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Review

A Journey through the Inter-Cellular Interactions in the Bone Marrow in Multiple Myeloma: Implications for the Next Generation of Treatments

by
Rosario Hervás-Salcedo
and
Beatriz Martín-Antonio
*
Department of Experimental Hematology, Instituto de Investigación Sanitaria-Fundación Jiménez Diaz (IIS-FJD), University Autonomous of Madrid (UAM), 28040 Madrid, Spain
*
Author to whom correspondence should be addressed.
Cancers 2022, 14(15), 3796; https://doi.org/10.3390/cancers14153796
Submission received: 4 July 2022 / Revised: 29 July 2022 / Accepted: 2 August 2022 / Published: 4 August 2022
(This article belongs to the Special Issue Immune Microenvironment and Cancer Progression)

Abstract

:

Simple Summary

Here, we describe the main interactions of multiple myeloma cells in the bone marrow with non-hematological and hematological immune cells that impact the disease’s progression and treatment resistance. Non-hematological cells in the bone marrow can secrete molecules that accelerate disease progression. On the other side, these interactions compromise immune cell activity, leading to immune evasion and disease progression. Deep knowledge of these interactions can lead to the design of improved treatments for multiple myeloma.

Abstract

Tumors are composed of a plethora of extracellular matrix, tumor and non-tumor cells that form a tumor microenvironment (TME) that nurtures the tumor cells and creates a favorable environment where tumor cells grow and proliferate. In multiple myeloma (MM), the TME is the bone marrow (BM). Non-tumor cells can belong either to the non-hematological compartment that secretes soluble mediators to create a favorable environment for MM cells to grow, or to the immune cell compartment that perform an anti-MM activity in healthy conditions. Indeed, marrow-infiltrating lymphocytes (MILs) are associated with a good prognosis in MM patients and have served as the basis for developing different immunotherapy strategies. However, MM cells and other cells in the BM can polarize their phenotype and activity, creating an immunosuppressive environment where immune cells do not perform their cytotoxic activity properly, promoting tumor progression. Understanding cell–cell interactions in the BM and their impact on MM proliferation and the performance of tumor surveillance will help in designing efficient anti-MM therapies. Here, we take a journey through the BM, describing the interactions of MM cells with cells of the non-hematological and hematological compartment to highlight their impact on MM progression and the development of novel MM treatments.

1. Introduction

Nowadays, it is widely accepted that the tumor microenvironment (TME) is a relevant component in tumors that modulates the response to cancer treatments affecting tumor progression. The TME consists of an extracellular matrix, a plethora of tumor cells, and a variety of non-tumor cells with complex interactions. These interactions, either through cell–cell contact or as soluble mediators, can accelerate tumor progression and the lack of response to cancer therapy [1]. Moreover, the knowledge of these interactions enables the development of non-immunotherapy [2,3,4] and immunotherapy strategies [5,6,7,8,9] in cancer patients.
Non-tumor cells in the TME, including endothelial cells, fibroblasts, and immune cells [7], modulate the responses to chemotherapy cancer treatments. For instance, chemotherapy agents that induce DNA damage, such as doxorubicin, trigger cytokine production by endothelial cells that decrease chemosensitivity of tumor cells to these treatments [10]. DNA-damaging agents also induce a senescence state in cells with the production of a senescence-associated secretory phenotype (SASP), a secretome rich in chemokines and growth factors that promote tumor progression [11]. Indeed, the secretion of SASP by endothelial cells in the TME includes IL6 secretion and chemoresistance development [12]. Tumor-associated macrophages (TAMs) with an M2-like phenotype provide a survival advantage to tumor cells in hypoxic conditions through IL6 receptor-mediated signals [13]; they protect tumor cells against paclitaxel, etoposide, and doxorubicin [14]. Moreover, platinum-based therapy supports monocyte differentiation to M2 macrophages, which associates with tumor progression [15].
Cellular components in the TME also influence the efficacy of radiotherapy treatments. Hence, radiotherapy activates fibroblasts, which become cancer-associated fibroblasts (CAFs). While some studies argue that CAFs promote tumor progression, others claim they are beneficial [16,17]. Thus, CAFs can secrete cytokines, such as IL32 that promote cancer cell invasion and metastasis [18]. However, CAFs in vivo depletion accelerates pancreatic cancer accompanied by epithelial-to-mesenchymal transition and enhanced T-regulatory (regs) cells that is reversed with anti-CTLA4 immunotherapy [19].
Immune cells and their secretome also shape the TME [1], impacting cancer progression and the efficacy of immunotherapy treatments [20]. For instance, tumor-infiltrating cells (TILs) in the TME are the basis for developing immunotherapy strategies based on immune checkpoint inhibition (ICI) that try to reactivate the tumor immune-surveillance activity of TILs [9]. Radiotherapy can promote tumor-specific immunity by activating dendritic cells (DCs) in the TME that support tumor-specific effector CD8 T cells [21]. Moreover, immunotherapy strategies based on the infusion of chimeric antigen receptor (CAR)-modified T cells have significantly improved the treatment of hematological malignancies [22,23,24,25]. However, in solid tumors, the barriers imposed by the TME [26] have delayed the development of efficient CAR-T cell therapies. Age also seems to play an essential role in the immune cells’ activity and, therefore, in immunotherapy. Thus, in hematological malignancies, pediatric patients with acute lymphoblastic leukemia (ALL) have achieved outstanding responses after treatment with CAR-T cells [22]. However, in adult patients with multiple myeloma (MM) [27], a disease where aging is a risk factor and where the TME is more relevant than in ALL, a proportion of patients end-up relapsing. In MM, the progression of the disease is drastically affected by the TME, either by soluble factors or cell–cell interactions in the bone marrow (BM) [28]. Moreover, relapses after administration of CAR-T cells [27], and the lack of efficacy of ICI therapies with significant toxicities in MM [25] might be partly explained by the impact of non-immune and immune cell interactions in the TME.
Here, we will take a journey through the BM, describing the interactions of plasma MM cells with cells of the non-hematological compartment to highlight the impact that these interactions have on the survival of tumor cells and the development of novel MM treatments. Moreover, we will describe the main differences found in the different immune cell subsets in the BM of MM patients that might lead to deficient tumor surveillance and failure of immunotherapy treatments in MM.

2. Impact of Interactions between Non-Hematological Cells and MM Cells in the BM

2.1. Extracellular Matrix (ECM)

MM is a hematologic malignancy characterized by clonal proliferation of plasma cells in the BM [29]. However, different trafficking events of MM cells allow them to reach distinct niches from the BM, re-circulate to the BM, and finally egress from the BM during the extramedullary stage of the disease [28]. When MM cells re-enter the BM, they use the BM sinusoids, where the interaction CXCR4/CXCL12 is critical to promote both MM cell homing and retention in the BM [30]. In the BM, MM cells will interact first with proteins in the ECM, a complex layer of proteins that serves as a scaffold for many cells. Interactions between MM cells and the ECM are required for cell proliferation, migration, and survival [31]. Specifically, CD138 and VLA-4 on MM cells directly interact with the ECM proteins, such as collagen type 1 and fibronectin. The binding of VLA-4 to fibronectin induces activation of nuclear factor-kB (NFkB), inducing tumor cell survival and cell adhesion-mediated drug resistance [32]. These interactions generate a welcome and growth-supporting environment that stimulates the dissemination of the malignant plasma cells and results in the upregulation of anti-apoptotic proteins and cell cycle dysregulation [33]. Strategies used in the clinic to disrupt these MM–ECM interactions and reduce cell adhesion-mediated drug resistance include the CXCR4 inhibitor AMD3100 or the proteasome inhibitor bortezomib, which downregulates VLA-4 on MM cells [34], leading to the de-adhesion of MM cells from the BM and turning them more sensitive to therapeutic agents [35]. However, although these agents can enhance the efficacy of treatments by disrupting these interactions, they also contribute to the mobilization of MM cells from the BM into the circulation, promoting extramedullary disease [36].

2.2. Control of the Stroma by BM Mesenchymal Stromal Cells (BM-MSCs)

In physiological conditions, the primary cell population in the BM stroma, known as bone marrow mesenchymal stromal cells (BM-MSCs), support the maintenance and differentiation of hematopoietic lineages, regulate bone homeostasis and contribute to the spatial delimitation of the endosteal and vascular niches [37]. However, in MM, BM-MSCs, as part of the BM microenvironment, play a crucial role in the pathology of the disease. Despite being at low proportions in the BM (0.01 to 0.001% of mononuclear cells) [38], BM-MSCs are the main population among BM stromal cells that interact with MM cells by direct cell–cell contact or through paracrine secretion of different pro-survival cytokines. Thus, for instance, binding VLA-4 on MM cells to VCAM-1 on BM-MSCs promotes activation of NFkB increasing MM cell survival and proliferation [39]. Moreover, the integrin lymphocyte function-associated antigen 1 (LFA-1) on MM cells and its transmembrane binding partner Mucin 1 (MUC1) bind to ICAM-1 in adjacent BM-MSCs, resulting in the activation of different pathways associated with poor prognosis and disease progression in patients [40]. The strong impact of the interactions with BM-MSCs in the physiology of MM cells and their acquisition of multidrug resistance phenotype justifies their consideration as targets for MM therapy. Indeed, some drugs have been developed to disrupt these interactions and tested in MM patients, such as Natalizumab, a recombinant humanized IgG4 monoclonal antibody (MoAb) which binds α4 integrin impairing the interaction VLA-4/VCAM-1 (NCT00675428). Other promising approaches have been preclinically evaluated, such as the LFA-1 inhibitor LFA878 [41].
Soluble mediators are also required for MM plasma cell survival and proliferation in the BM. Thus, MM cells induce BM-MSCs to secrete cytokines that will be used for their benefit. Specifically, the main secreted cytokine is interleukin-6 (IL6), which is involved in MM growth, survival, migration, and drug resistance [42]. In turn, MM cells use IL6 to enhance the secretion of vascular endothelial growth factor (VEGF) and basic fibroblast growth factor (bFGF). Then, both VEGF and bFGF bind to their receptors on BM-MSCs, re-stimulating IL6 production [43]. Whereas inhibition of IL6 has not shown clinical benefit in MM [44], blocking of IL6 receptor with tocilizumab has shown efficacy in MM patients [45]. Furthermore, MM cell interactions with BM-MSCs cells are mediated through Notch pathways and Dickkopf-1 (DKK1), which induce the secretion of IL6, VEGF, and insulin-like growth factor (IGF-1) in BM-MSCs [46,47]. Moreover, MSC-derived exosomes contain the long intergenic noncoding RNA LINC00461, which promotes MM cell proliferation and suppresses the beneficial effect of dexamethasone treatment. Indeed, the knockdown of LINC00461 enhances the beneficial impact of dexamethasone in preclinical studies [48].
B-cell activating factor (BAFF) and a proliferation inducing ligand (APRIL) are additional mediators with a protective effect on MM cells [49]. BAFF is a member of the tumor necrosis factor (TNF) family expressed on the surface of BM-MSCs and as a soluble form. BAFF stimulates B cell growth, and ligation of BAFF leads to increased proliferation and survival of MM cells [50]. APRIL is a secreted protein by BM-MSC that binds to B-cell maturation antigen (BCMA) and to transmembrane activator and calcium-modulator and cyclophilin ligand (TACI) on MM cells [51]. Therefore, APRIL-based CARs target MM cells expressing either BCMA or TACI with high efficacy at pre-clinical levels [52]. Moreover, BM-MSCs also protect MM cells against the lytic machinery of CAR-T cells [53].
Another member of the TNF family involved in this stromal training is TNFα, which induces the expression of adhesion molecules, such as LFA-1, ICAM-1, VCAM-1, and VLA-4 on MM cells, as well as ICAM-1 on BM-MSCs, resulting in increased binding of MM cells to BM-MSCs and further enhancing IL6 secretion [54]. These paracrine loops are critical for maintaining the constant growth of MM cells through the activation of different signaling pathways. In addition, MM cell interactions with BM-MSCs, added to the senescent status of cells in the BM in MM, further enhance the secretion of cytokines, chemokines, and soluble factors secreted by BM-MSCs to the BM milieu, which induce further MM proliferation and survival. TNFα, crucial in inflammation, is related to bone resorption and enhanced in MM patients. Thus, targeting TNFα could improve MM responses to treatments [55]. However, reports in inflammatory diseases suggest that anti-TNF-α inhibitors enhance the risk of having future hematological malignancies [56].
In summary, these interleukins and growth factors secreted by BM-MSCs cause tumor growth and drug resistance, limiting current MM treatments’ impact. Indeed, they are promising targets for developing anti-MM therapies that avoid the negative effect of BM-MSCs on dexamethasone treatment [48], on CAR-T cell therapies [53], or the negative impact of IL6 secretion. Thus, tocilizumab, an anti-IL6R [57], BHQ880, a monoclonal antibody against DKK1 [58], or tabalumab, a potent and selective fully human IgG4 MoAb with neutralizing activity against membrane-bound and soluble BAFF [59] are strategies that could be added to MM treatment.

2.3. Osteoclast/Osteoblast Imbalance in the Endosteal Niche

As previously mentioned, MM cells not only interact with the stromal compartment they also alter the endosteal and vascular niches in the BM. In the endosteal niche, healthy bone remodeling in the BM is maintained by a balance between bone formation (osteoblastogenesis) versus bone degradation (osteoclastogenesis). However, MM cells alter this dynamic balance, enhancing bone resorption to enable space for MM proliferation, causing the osteolytic lesions characteristic of myeloma bone disease (MBD) in around 80–90% of MM patients [60]. The negative impact of MBD on patient survival, quality of life, and public health costs has led to the development of different approaches to block MM-endosteal niche interactions. Strategies for patients to treat and avoid MBD have recently been reviewed [61]. Here, we describe which interactions of MM cells with cells in the endosteal niche, including BM-MSCs and other bone populations, such as osteoclasts and osteoblasts, accelerate MBD.
MM cells, through different mechanisms, upregulate osteoclast activity and differentiation resulting in imbalanced bone resorption, causing the osteolytic lesions of the MBD [62]. Specifically, MM cells secrete macrophage inflammatory protein-1α (MIP1α) and MIP1β that directly activate osteoclast formation and activity [63,64]. In turn, osteoclasts secrete IL6 to stimulate their self-proliferation and the proliferation of MM cells [65]. This interaction upregulates Chondroitin synthase 1 (CHSY1), which induces Notch signaling promoting MM cell survival and stimulating the recruitment of osteoclast precursors to increase bone resorption [66]. Macrophage-colony stimulating factor (M-CSF) and receptor activator of NFkB (RANK) ligand (RANKL) are additional factors required for osteoclast differentiation. Osteocytes produce RANKL, which promotes osteoclast activity through binding to RANK on osteoclastic lineage cells [67]. Nevertheless, MM cells’ interaction with BM-MSCs leads to the secretion of RANKL by BM-MSCs, further stimulating osteoclast activation and differentiation and enhancing bone lysis. This interaction also leads to the production of cytokines by BM-MSCs, such as IL6, which further promotes osteoclast growth [68]. In this way, amino-bisphosphonates have been administered in MM patients as first-line therapy for MBD due to their capacity to inhibit osteoclast activity [69]. Moreover, Denosumab, a fully human monoclonal antibody against RANKL, has also shown clinical benefit in MM patients [70]. Denosumab inhibits the development and activity of osteoclasts, decreases bone resorption, and increases bone density [71].
On the other hand, MM cells prevent osteoblast progenitor cell maturation and inhibit osteoblast activation, to continue impairing bone formation. Direct cell–cell interactions of MM cells through binding to VCAM-1 on osteoblast progenitors downregulate RUNX2 activity, essential for osteoblast differentiation [72]. Moreover, osteoblasts and BM-MSCs produce osteoprotegerin (OPG), which prevents the development of bone alterations caused by osteoclast/osteoblast imbalance. However, the binding of VLA-4 on MM cells to VCAM-1 on BM-MSCs decreases OPG secretion, forcing the balance in favor of osteoclasts and bone degradation [73]. Disrupting this VLA-4/VCAM-1 interaction with monoclonal antibodies, such as Natalizumab, could prevent bone lysis in MM patients, as described in preclinical models [74]. On the other hand, BHQ880, the DKK1-neutralizing antibody, can increase osteoblast differentiation, blocking the negative effect of MM cells on osteoblastogenesis and reducing IL6 secretion in MM patients [75].

2.4. Angiogenesis Promotion in the Vascular Niche

During the development of MM, an alteration in the neovascularization process occurs that affects the vascular niche. Neovascularization is the formation of new vessels from existing ones through endothelial cells (angiogenesis) or from endothelial precursors (vasculogenesis). Interactions between plasma cells and the BM microenvironment can modify this biological process [76,77,78].
Angiogenesis in cancer involves an early balanced avascular phase that gives rise to an uncontrolled and unlimited in-time vascular phase [79]. In the context of MM, Rajkumar et al. demonstrated that the BM microvascular density is increased in MM patients [80]. In this environment, the accumulation of MM cells in the BM generates hypoxic tumors highly expressing hypoxia-inducible factor-1 alpha (HIF-1α). HIF-1α will upregulate angiogenesis to deliver oxygen and nutrients and remove catabolites [81]. Different cytokines control angiogenesis, such as VEGF, fibroblast growth factor-2 (FGF-2), and hepatocyte growth factor (HGF). In MM, MM plasma cells become CD45-negative and produce VEGF [82]. Moreover, endothelial cells in the BM of MM modify their phenotype, expressing surface receptors related to angiogenesis, such as VEGFR-2 and Tie2/Tek, and increased expression of the β3-integrin and endoglin [83]. This differentiated phenotype in endothelial cells of the BM enhances MM cell interaction with the new-formed blood vessels and favors the entry and dissemination of MM cells into the circulation. This angiogenic phenotype in MM cells can also be induced by oncogenes, such as C-MYC, C-FOS, C-JUN, and ETS-1, which become active as a consequence of the genetic instability and immunoglobulin translocations in MM [84].
On the other hand, the differentiation of endothelial progenitors termed angioblasts during embryogenesis causes the development of the vascular system, known as vasculogenesis [85]. Studies suggest that vasculogenesis is responsible for the neovascularization in the BM in MM [86,87]. Indeed, endothelial markers such as VIII-related antigen (FVIII-RA), vascular endothelial-cadherin (VE-cadherin), VEGFR-2, TIE/Tek, and CD133 are expressed in endothelial cells of the neovessel wall [88]. Moreover, interactions of MM cells with BM-MSCs in the BM also impact vasculogenesis. Thus, MM cells stimulate BM-MSCs in the vascular niche to secrete HGF, VEGF, and IL8, further inducing neovascularization [89]. In turn, endothelial cells in MM will produce IGF1 and IL6 to promote MM cell growth, causing an autocrine loop in endothelial cells, which will enhance their production of VEGF, platelet-derived growth factor (PDGF), Ang-1, HGF, and IL1 to promote angiogenesis constantly [90].
The relevance of angiogenesis in the development of MM has led to the development of different treatments targeting this process. For instance, amino-bisphosphonates that inhibit osteoclasts also present anti-angiogenic activities and are administered in MM patients as supportive therapy for bone disease [69]. Ria et al. reviewed different strategies in MM mainly based on VEGF inhibition, such as monoclonal antibodies anti-VEGF (Bevacizumab) [91]. However, the addition of bevacizumab to anti-MM therapies did not result in a significant improvement in the outcome of patients [92,93]. Derivatives of quinolone and quinazoline, which inhibit a variety of tyrosine kinases, including VEGFRs, EGFR, and PDGFR have also been tested in MM patients. Despite their in vitro activity and reduced plasma levels of VEGF in treated MM patients, no responses or clinical benefits were achieved [94,95]. These disappointing results inhibiting a single proangiogenic cytokine could be related to the role played by hypoxia and other active pro-angiogenic pathways in the BM microenvironment, and greater efficacy could be feasible with drugs that simultaneously block multiple cytokines. Moreover, immunomodulators (IMIDs), such as thalidomide or lenalidomide, have revealed anti-angiogenic activity and inhibition of the secretion of angiogenic cytokines in MM patients [96,97].
To summarize, interactions between MM cells and cells that do not belong to the hematological BM compartment form a feedback loop that leads to bone destruction, angiogenesis, and tumor expansion in the BM. Unraveling these interactions has allowed the development of novel treatments for MM patients combining different strategies to block several molecules simultaneously. The most pertinent inter-cellular interactions, their impact, and the possible options of treatments are summarized in Figure 1 and Table 1. However, as we will explain in the next section, immune cells also play a relevant role in MM progression.

3. Impact of Interactions between Immune Cells and MM Cells in the BM of MM Patients

On the other hand, immune cells make up the hematological compartment of the BM, where the crosstalk between MM plasma cells and immune cells, from both myeloid and lymphoid lineage, plays a critical role in MM growth and maintenance. However, while non-hematological cell populations are partners that MM cells use for their benefit, the immune cell compartment is naturally composed of anti-tumor cells involved in tumor immunosurveillance [149]. However, MM cells create an immunosuppressive microenvironment and evade the immune system, a dynamic process encompassing multiple aspects of tumor cell–immune cell interactions [150] that favors MM proliferation and resistance to treatments [151]. In addition, the immune cells’ plasticity and capacity to polarize to different subsets enable the survival of normal and malignant plasma cells in the BM [152]. Another level of complexity comes with the deterioration of the immune system associated with aging, where MM represents an elderly population. Moreover, the accumulation and/or recruitment of immunosuppressive lymphoid and myeloid cells within the BM is another powerful mechanism during myelomagenesis [153].
This section describes relevant aspects of the different immune cell subsets in MM patients related to their inability to control MM progression. These interactions and how to avoid their detrimental impact are summarized in Figure 2 and Table 1.

3.1. Effector CD8 T Lymphocytes

The potential anti-MM activity of T cells in MM was suggested in the past with the observation that levels of CD3, CD4, CD8, and CD19 cell subsets in MM are associated with response to chemotherapy and survival [154]. Thus, the presence of T cell clones in MM associates with prolonged overall survival suggesting their anti-tumor activity [155]. Indeed, tumor-infiltrating lymphocytes (TILs), defined as the lymphocytic cell populations present in tumors, can be used to design adoptive cellular immunotherapy strategies [156]. In MM, TILs are defined as marrow-infiltrating lymphocytes (MILs). Adoptive transfer of MILs in MM patients demonstrated a direct correlation between tumor specificity of the MILs with clinical outcomes. Of interest, compared to peripheral blood (PB) lymphocytes, MILs show increased expression of CXCR4, which through CXCL12/CXCR4 could facilitate the trafficking of MILs to the BM [101]. An interesting approach to enhance the trafficking of MILs could be to modify them to over-express CXCR4 [104]. In MM patients receiving MILs, CD8 T cells are the main cytotoxic T cell subset. It was observed that a central memory (CM) phenotype in CD8 T cells of MILs at baseline was associated with achieving complete responses (CR), whereas patients with disease progression had a higher frequency of terminally differentiated effector T cells at baseline [101]. An approach to avoid terminally differentiated MILs could be adding a PI3K inhibitor during the production of MILs, that in CAR-T cells has shown efficacy in reducing the proportion of highly differentiated or senescent T cells [105].
Moreover, CD8 T cells can become exhausted due to prolonged antigen stimulation [157]. Exhausted T cells express immune checkpoint receptors, including programmed death-1 (PD-1), cytotoxic T-lymphocyte-associated antigen 4 (CTLA4), LAG-3, or T cell immunoglobulin and ITIM domain (TIGIT) that interact with their ligands PD-L1, CD80/CD86, MHC-II, and CD155, respectively, on tumor cells [102,103]. This interaction is disrupted with immune checkpoint inhibitors (ICI) and restores the anti-tumor activity of exhausted T cells [102,103]. However, despite the success in malignancies such as melanoma [158], ICI causes adverse side effects [159,160], and targeting the PD-1/PD-L1 axis has not offered any clinical benefit in MM [106], showing high toxicity that led to the halting of different clinical trials [25].
Of interest, anti-PD1 therapy acts on a specific subpopulation of exhausted CD8 TILs termed “progenitor exhausted” cells that retain poly-functionality, persist long term, and differentiate into “terminally exhausted” TILs. Progenitor exhausted CD8 TILs respond to anti-PD-1 therapy and control tumor growth [161]. T cells in MM are highly differentiated [162], which might explain the lack of success in ICI studies. Indeed, within the PD-1 positive population of MILs in MM, only the subset of less differentiated CM T cells are responsive to anti-PD-1, and terminally exhausted T cells associate with worse clinical outcomes after PD-1 inhibition [163]. In addition, the lack of expression of PD-1 in CD8 T cells in newly diagnosed MM patients could also explain the lack of efficacy of the disruption of PD-1/PDL-1 interaction, being TIGIT the most frequent immune checkpoint receptor expressed on T cells [100]. Indeed TIGIT targeting has shown benefits in pre-clinical models of MM [100].

3.2. CD4 T Cell Subsets

During MM progression, an alteration in the number and proportion of the different T cell subsets occurs. Specifically, a reduced CD4/CD8 ratio, with lower number of CD4 T cells and Th2 cells is observed [107]. Moreover, IL6 secretion by MM cells [164] and by activated CD3 T cells in MM inhibits the polarization of naïve CD4 T cells into Th1 cells enabling tumor escape [108]. Immunotherapy strategies to obtain a product with an optimized CD4/CD8 T cell ratio [110] could improve this imbalance observed in MM. Indeed a higher CD4/CD8 ratio in the leukapheresis products used to generate CAR T cells in MM correlates with higher responses [111].
Within the CD4 population, regulatory T cells (T-reg cells) are characterized by FOXP3 expression [165]. T-regs have an important immunosuppressive activity towards antigen-presenting cells (APCs) and effector T cells by direct cell–cell contact or soluble mediators that promote immunological tolerance [166]. A variety of studies show that T-regs are enhanced in different types of cancers and related to tumor progression, including hematological malignancies [167]. However, there are conflicting results concerning their number and function in MM [168]. Thus, some studies describe elevated frequencies of functional T-reg cells in newly diagnosed and relapsed patients compared to healthy volunteers [169], while others reported a reduction in their number [170,171], being these T-reg cells dysfunctional [170]. Although there are few studies of T-regs comparing the BM to PB in MM, published reports show that the frequencies of T-regs in both departments are similar and that increased numbers of T-regs in the BM correlate with shorter time to progression and reduced survival [112,113].
The suppressive activity of T-regs in MM has been demonstrated in different studies via IL10 and TGFβ secretion that inhibit dendritic cells and block CD4 T cell-mediated generation of CD8 T cell cytotoxic activity [115]. Inducible T cell co-stimulator (ICOS) and CTLA-4 and expressed by T-regs are involved in their suppressive function [116]. Indeed, MM cells can directly generate functional T-reg cells contact-dependent through ICOS/ICOS-L. These T-regs can be inhibited with anti-ICOS-L MoAb [114]. In MM patients receiving MILs, the baseline percentage of T-regs was lower in patients who achieved a CR compared to those with disease progression. However, on day 360, the percentage of T-regs was normalized, reaching similar levels in all groups, with the CR patients showing the greatest increase [101].
In MM, treatment with talquetamab, a bispecific mAb against the G protein-coupled receptor (GPRC5D), expressed on MM cells, enhanced the anti-MM activity of CD4 conventional T cells but also of T-reg cells. However, T-reg cells presented lower anti-MM activity than conventional CD4 T cells, and seemed to ameliorate the activity of CD4 T cells with decreased production of IFNγ, TNFα, and IL2 [109].
On the other side, some reports demonstrate that higher numbers of T-regs in tumors associate with better prognosis in patients [172], suggesting that the exact prognostic significance of T-regs cells is still unclear, and further studies need to be done. For instance, preclinical studies based on a transient T-reg depletion have demonstrated immune control of MM and prevented disease progression [117].
Th17 cells are pro-inflammatory CD4 T cells that share a common precursor with T-reg cells, where different cytokines will promote the differentiation into one cell subtype or another [173]. Thus, TGFβ favors the formation of T-reg cells. However, in the presence of IL6, IL21 expression is enhanced, activating downstream signaling pathways that, with TGF-β, lead to the differentiation of Th17 cells [118]. In addition, Th17 and T-reg cells can polarize each other [173]. Th17 cells promote MM growth [119] and cause osteoclast-dependent bone damage [174]. Indeed, Th17 cell levels increase further in refractory disease [175] and MBD [176]. Moreover, IL17 production, due to an increased Th17 cell number, induces osteoblast cell death through pyroptosis with the release of IL1β [120] and cooperates with RANKL to further activate osteoclasts enhancing tumor growth and promoting MBD in MM [119]. Newly diagnosed MM patients present a higher number of Th17 cells and IL17 in serum, with decreased T-reg cells. Thalidomide treatment normalized the ratio of Th17 and T-reg cells in PB [121]. Indeed, the efficacy of MoAbs targeting IL17 has been assessed successfully at pre-clinical stages to treat MM [122].

3.3. The Impact of Age in T Lymphocytes in MM

The lack of efficacy of ICI in MM has suggested that other dysfunctionalities in T cells might be more relevant in MM, such as the presence of T cell “immunosenescence”. MM is a disease related to the elderly, and the immune system is highly impacted by age. Specifically, “immunosenescence” refers to the deterioration of the immune system that affects T cells, macrophages [177], and natural killer (NK) cells [178], leading to dysfunctional immune responses. In T cells, chronic viral infections, inflammatory diseases, a replacement of BM cellular components by adipocytes, and a thymic involution occurring with aging cause immunosenescence. Immunosenescence is characterized by a loss of the naïve and stem cell memory (SCM) T cell compartments as they differentiate, producing an accumulation of oligo-clonal memory and pro-inflammatory effector T cells that present shorter life and lower proliferative capacity [179,180,181,182]. Immunosenescence also reduces the capacity of T-reg cells to suppress self-reactive T cells and preserve immune homeostasis [180,181]. Moreover, T cell immunosenescence is accelerated with chemotherapy treatments [124] and after therapy with ICIs [125]. In general, most studies agree that immunosenescent T cells lose the naïve CD8 and CD4 T cell compartment, with loss of CD27 and CD28, increased expression of CD57, KLRG1, and PD-1, and secretion of large amounts of IFNγ and TNFα, IL2, IL4, IL10, and IL6 [11,183]. In MM, a higher number of immunosenescent T cells than healthy donors have been described [162] with low proliferative capacity and expression of CD57, KLRG1, CD160, CD28, PD1low, and CTLA4low [123]. Indeed, adoptive cell therapy with MILs in MM showed that the presence of less differentiated CM CD8 T cells correlated with achieving complete responses [101]. Moreover, the pro-inflammatory phenotype of immunosenescent T cells might explain the high number of adverse events observed in MM patients treated with ICIs [25].
In addition, immunotherapy based on administering CAR-T cells has achieved outstanding responses in pediatric patients, where CAR-T cells persist over the years in PB as guardians [22]. However, in MM, patients relapse despite achieving complete responses with a lack of persistence of CAR-T cells [27]. The presence of T cell immunosenescence in MM might partly explain the lack of persistence of CAR-T cells and suggest novel strategies to reverse T cell immunosenescence. The reversal of T cell immunosenescence is a field in development. Different approaches are being tested, including the recombinant growth hormone, that in healthy donors reversed immunosenescence partially with the regeneration of the thymus, a decline in the PD-1 positive CD8 T cells, and an increase in the naïve CD4 and CD8 T cells [184].
Cytokines also influence the differentiation of T cells. In this regard, the production of CAR-T cells and MILs provide a window to add different cytokines and compounds that modify the immunosenescence state of T cells that patients receive. Thus, IL-7, through binding to its receptor IL-7Rα, promotes the differentiation of naïve T cells into effector T cells [185]. Indeed, the addition of IL7 to IL15 during the production of CAR-T cells for MM accelerated the differentiation of CAR-T cells leading to a shorter CAR-T cell persistence in vivo in preclinical models. However, the production of CAR-T cells with IL15 obtained a product less differentiated that demonstrated the highest in vivo persistence compared to IL2 and the combination of IL7 and IL15 [126].
Kinases also regulate T cell senescence, and their inhibition has a high potential to avoid immunosenescence. Thus, inhibition of p38-MAPK in CD4 T cells enhances their survival after TCR activation [186]. Moreover, sestrins bind to and coordinate Erk, Jnk, and p38 MAPK activation in T cells within a complex termed sMAC. Compared to the inhibition of individual MAPKs, sestrin ablation in T cells from old humans disrupted the sMAC complex restoring immune function and antigen-specific functional T cell responses [127]. mTOR pathway is also involved in differentiating naïve CD4+ T cells into Th1 or Th17 cells T cells [187]. Thus, in older individuals, mTOR inhibitors, such as rapamycin or everolimus, have improved their immune function [188]. However, rapamycin also suppresses the anti-inflammatory effects of glucocorticoids in human monocytes and myeloid dendritic cells [189]. Inhibition of PI3K during the production of CAR-T cells for MM also provides a less differentiated product associated with a higher duration of response [105]. Adding these compounds only during the production of T cells that patients will receive will avoid the side effects observed after in vivo administration of these drugs.

3.4. NK Cells

NK cells are anti-tumor and anti-microbial cells of the innate immune system equipped with a wide array of activating and inhibitory receptors that activate or inhibit their activity through different mechanisms such as granzyme and perforin release, death receptor pathways, and release of additional pro-inflammatory molecules [137,190,191,192,193]. There are two main populations of NK cells in PB, the mature and cytotoxic NK CD56dim and the immature and immunoregulatory CD56bright NK cells [137,192]. Their anti-tumor activity and potential as an allogeneic source of immune cells have made NK cells an attractive target for immunotherapy in different malignancies, including MM [137,194]. A recent meta-analysis study in solid tumors showed that NK cell infiltration associates with increased overall survival in cancer patients. In detail, NK infiltration is more common in earlier stage and higher-grade tumors. Moreover, infiltrating NK cells in intraepithelial regions impacts survival more than infiltrating NK cells in the adjacent stroma [195].
NK cells recognize MM cells through activating receptors, including NKG2D, NKP30, 2B4, NKp80, or DNAM-1, which interact with their ligands in MM cells [137,190]. In newly diagnosed MM patients, the frequency of NK cells in PB does not differ from healthy donors [196]. However, NK cells in MM impair their cytotoxic activity with decreased expression of the activating receptor CD161 and increased expression of the inhibitory CD158a receptor [196]. In addition, MM cells downregulate or block NKG2D and NKp80 on NK cells, inhibiting their activity [128]. NK cells also express PD-1, that in MM patients is up-regulated and interacts with PD-L1 on MM cells [129]. BM stromal cells-derived IL6 inhibits NK cell activity [131] and induces PD-L1 expression in MM cells, impacting the anti-MM activity of NK and T cells [132,133]. Moreover, MDSCs, through tumor-derived IL1β, impair NK cell development and activity [134]. In addition, the expression of chemotactic factors and their receptors in the BM of MM affect the attraction of immune cells. Specifically, NK cells express CXCR3 to enable migration to the BM when required. During MM progression, chemokine ligands involved in the migration of NK cells are imbalanced, including increased levels of CXCL9 and CXCL10 and decreased levels of CXCL12. Moreover, a down-regulation of CXCR3 on NK cells occurs. Altogether drives NK cells outside the BM, weakening their anti-MM activity in the BM [135]. Therefore, altered interactions of NK cells with MM cells impair NK cell anti-tumor activity and are targets for developing strategies that reestablish the anti-MM response of NK cells. Many approaches have been proposed to improve NK cell activity [136,137]. These strategies could be the combination of NK cells with IMiDs and MoAbs that activate antibody-dependent cell cytotoxicity (ADCC) of NK cells. For instance, Daratumumab (anti-CD38), VIS832 (anti-CD138), and Dacetuzumab (anti-CD40) have demonstrated potential in preclinical studies. Bispecific and trispecific killer engagers (BiKEs/TRiKEs) also can redirect NK cells to tumor cells. Antibody recruiting molecules (ARMs) bind a tumor-associated antigen with endogenous IgG that will induce NK-mediated ADCC. NK cell activators, such as ALT-803, an IL-15 superagonist, stimulate NK cells and T cells, and finally, CAR-NKs targeting SLAMF7, CD138, or NKG2D ligands MM antigens have demonstrated pre-clinical efficacy [136,137].
In addition, decidual NK (dNK) cells represent a transient population present during the first months of pregnancy. dNK cells are CD56bright and highly angiogenic through the production of proangiogenic factors, including VEGF, PlGF, CXCL8, IL10, and angiogenin [197,198,199]. It has been suggested that the recruitment of conventional CD56bright PB-NK cells could contribute to their origin [200,201]. This angiogenic or “nurturing” role of dNK cells required during early pregnancy presents homologies to the angiogenic processes during tumor progression. In this regard, in relapsed/refractory and newly diagnosed MM patients, the CD56bright NK cell subset, highly activated, is the prevailing NK cell subset in both BM and PB, being these differences more pronounced in the BM [130]. Therefore, further studies in MM patients should add additional markers to characterize better a possible angiogenic activity of CD56bright NK cells detected in the BM of MM patients. Of interest, in vitro expanded NK cells administered in immunotherapy acquire a CD56bright phenotype [202,203]. Thus, a possibility to improve clinical studies that infuse expanded NK cells in MM patients could be the previous selection of CD56dim mature NK cells.

3.5. Regulatory B Cells

B-reg cells represent another essential immunosuppressive arm in the adaptive immune system that is affected by their interaction with MM cells. B-reg cells maintain immune tolerance and suppress autoimmune and inflammatory responses through secretion of IL35, TGFβ, and IL10, as well as expression of inhibitory molecules, such as PD-L1 [204]. In healthy donors, IL10 secretion of B-reg cells suppresses CD4 T cell proliferation and the release of IFN-γ and TNF-α by CD4 T cells, inhibits CD4 T cell differentiation into Th1 and Th17 cells, and favors CD4 T cell polarization into T-regs [138]. In the TME, tumor-released autophagosomes induce this B-reg population [205]. Despite their poorly described role in MM, B-reg cells have become essential players increasing during the initial stages of MM and head for extinction in relapsed or refractory MM [206]. Thus, newly diagnosed MM patients have no differences in PB B-reg cells compared to healthy donors. However, B-reg cells accumulate in the BM of newly diagnosed MM patients rather than in PB, where MM cells promote the survival of B-reg cells. Moreover, B-reg cells in PB and BM are higher at MM diagnosis than after response to therapy, and, finally, at relapse, they are too low to be detected. Moreover, MM B-regs avoid NK-ADCC against MM cells [139]. Despite the relevant role of B-reg cells in the progression of MM, strategies to target them in the clinic have not been described yet. Novel research to decipher cellular interactions of B-reg cells with other cells and how B-reg cells exert their suppressive activity is required first to foresee the possible implications of their targeting.

3.6. Tumor-Associated-Macrophages (TAMs)

Tumor-associated-macrophages (TAMs) abundant in the MM microenvironment, can protect MM cells from chemotherapy-induced apoptosis and exert anti-tumor activity [207,208]. Even though macrophages present high plasticity, they are traditionally classified into: (1) M1 activated macrophages with anti-tumor activity that secrete pro-inflammatory cytokines; or (2) the alternatively activated M2 macrophages with immunosuppressive activity. Indeed, several clinical studies in MM patients have associated a high infiltration of M2 macrophages in the BM with poor prognosis and poor response to current treatments, while patients with increased infiltration of M1 macrophages showed better outcomes [209]. M1/M2 polarization will rely on signals present in the environment. Thus, pro-inflammatory cytokines promote M1 differentiation, and immunosuppressive ones drive the differentiation towards an M2 phenotype [210]. MM cells influence the phenotype and recruitment of macrophages in the BM. Thus, CXCL12 production by MM cells and BM-MSCs increases monocyte recruitment through the CXCL12/CXCR4 axis and induces M2 macrophage polarization. These CXCR4-M2-educated macrophages are grown in the BM of MM compared to healthy controls, support MM cell proliferation, protect them from chemotherapy, and suppress T-cell proliferation and activity [140]. Of interest, MM cells secrete extracellular vesicles (EVs) that polarize recruited monocytes to an M2 phenotype with subsequent release of M2-associated cytokines such as IL6, IL10, IL8, and TNFα that promote tumor proliferation. Circulating miR-16 in serum impairs these events. Indeed, high miR-16 levels associate with prolonged survival in MM patients [211]. Moreover, soluble secreted forms of M2 macrophage receptors, such as CD206 and CD163, and chemokines like CCL2, have been proposed as biomarkers for disease progression, prognosis, and treatment response [141,142]. Moreover, macrophages directly affect immune evasion using their macrophage immune checkpoint. The binding of CD47 in the membrane of MM cells to signal-regulatory protein alpha (SIRPα) receptor on the surface of macrophages leads to downstream signaling within the macrophages, resulting in inhibition of phagocytosis activity [143].
The relevance of macrophages in MM is evidenced by increasing strategies used in preclinical and clinical studies to counteract their supportive role in MM progression. As mentioned, the CXCR4/CXCL12 axis contributes to MM cell adhesion and migration and promotes monocyte recruitment and differentiation towards a proangiogenic and immunosuppressive M2-like phenotype. In preclinical studies, the inhibition of CXCR4 significantly suppressed monocyte recruitment to the BM [140]. For that reason, analyzing the impact of AMD3100 (CXCR4 inhibitor) on macrophages in MM patients could reveal positive results. Once in the BM, depletion of BM resident macrophages is a strategy to reduce macrophage tumor support with promising preclinical results, proving that macrophage depletion can limit MM disease burden [144]. Other targeted therapies block the pro-tumor functions of TAMs, reprogramming them to reduce their immunosuppressive M2 phenotype and promote M1 phenotype. Currently, the most common approach for targeting macrophages involves inhibiting the CSF1 receptor (CSF1R), which regulates the migration, differentiation, and survival of macrophages and their precursors [145]. In MM, a recent preclinical study has demonstrated a significant reduction in tumor burden following treatment with the anti-CSF1R antibody [212], suggesting that targeting macrophages, via CSF1R, in combination with standard therapies, may be a promising therapeutic strategy in MM. Finally, targeting immune checkpoints in macrophages has been an emerging topic [213]. Currently, some clinical studies aim to inhibit the CD47-SIRPα immune checkpoint using various strategies, including anti-CD47 antibodies (SRF231: NCT03512340 and AO-176: NCT04445701) or SIRPα-IgG1 Fc fusion proteins (TTI-621: NCT02663518 and TTI-622: NCT03530683). In general, TAM-targeting therapy represents a promising treatment for MM patients and could improve current MM cell therapies, overcoming unresponsiveness and drug resistance.

3.7. Myeloid-Derived Suppressor Cells

(MDSCs) are a heterogeneous subset of immature myeloid progenitor cells that inhibit innate and adaptive immune responses, induce T-reg differentiation, promote angiogenesis, and even differentiate themselves into functional osteoclasts, promoting tumor growth [28]. MDSCs can be further divided into CD14+ monocytic (M-MDSC) and CD15+ granulocytic (G-MDSC) subsets being G-MDSC increased in the PB of MM patients [214]. Murine models show that MDSCs accumulate in the BM during MM progression in the early stages of the disease while circulating myeloid cells increase at later stages, and MDSC targeting reduces tumor load [215]. Moreover, the frequency of M-MDSCs in PB predicts outcomes after lenalidomide-dexamethasone treatment, where failure to achieve a response associates with an increase in M-MDSC frequency after treatment [216].
MDSCs perform an important suppressive activity of CD8 T cells and NKT cells in the BM. To achieve these suppressive functions, MDSCs produce arginases (ARG1), reactive oxygen species (ROS), cyclooxygenase-2 (COX2), inducible NOS (iNOS), IL6, IL10, IL18, and reduce metabolic factors required for T-cell activation. Moreover, MM cells induce MDSCs development from PB mononuclear cells in healthy donors, suggesting the relevance of bi-directional cell–cell communication [146]. In addition, soluble factors from MM cells, such as IL10, CCL5, MIP-1 or large amounts of IL6 generate MDSCs with T cell suppressive ability through Mcl-1 upregulation that enhances MDSCs survival [215]. In addition, BM stromal cells-derived exosomes in MM induced survival of MDSCs through STAT3 and STAT1 pathways and increased anti-apoptotic proteins Bcl-xL and Mcl-1 [217].
The relevance of MDSCs has been translated to patients. Thus, dual targeting of MM cells and MDSCs with biotherapeutic agents, such as Daratumumab [147], has emerged as a promising new therapeutic option with high potential, as recently reviewed by Uckun [218]. On the other hand, the α-chain of the IL3 receptor, known as CD123, is highly expressed on MDSCs [219]. For that reason, several biotherapeutic agents targeting CD123 have been developed, including the CD123-directed recombinant human IL3 fusion toxin Tagraxofusb (SL-401). SL-401 has been assessed in combination with the standard of care (NCT02661022) in relapsed/refractory MM patients with promising early evidence of clinical activity. Altogether, these studies suggest that therapies targeting MDSCs might overcome the immunosuppressive environment in the BM of MM and increase the anti-tumor effect of additional treatments for MM patients.

4. Conclusions

To conclude, tumor cells in MM develop a smart network in the BM with non-hematological and hematological cells that create an environment that nurtures and protects them from traditional chemotherapy and novel based-immunotherapy treatments. Interactions with cells that do not belong to the hematological BM compartment form a feedback loop that leads to bone destruction, angiogenesis, and tumor expansion in the BM. Moreover, whereas immune cells are supposed to perform tumor surveillance, MM cells and non-hematological cells in the BM can polarize the phenotype and activity of immune cells leading to immune evasion. Unraveling these interactions has allowed the development of novel treatments for MM patients. In addition, MM patients represent an elderly population with immunosenescent T cells, which might explain the lack of efficacy of some immunotherapy treatments.
Finally, finding the most appropriate treatment for each MM patient among all the available treatments is an urgent need that requires first to have a global picture of the proportion of the different cell subsets in the TME. Deciphering the cellular imbalance in the TME will help select the best treatment combination that could restore this imbalance for each patient. Indeed, novel technologies based on multi-immunofluorescence allow deciphering cell–cell interactions in the TME and the phenotype of cells that will help treat patients.

Author Contributions

Both authors conceived the study. Both authors wrote and reviewed the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by Fondo Europeo de Desarrollo Regional (FEDER): Instituto de Salud Carlos III. Project PI20/00991; and Miguel Servet Program type I: CP21/00111.

Acknowledgments

Figures were made with Biorender.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Etxebeste-Mitxeltorena, M.; Del Rincón-Loza, I.; Martín-Antonio, B. Tumor Secretome to Adoptive Cellular Immunotherapy: Reduce Me Before I Make You My Partner. Front. Immunol. 2021, 12, 717850. [Google Scholar] [CrossRef] [PubMed]
  2. Li, W.; Ng, J.M.-K.; Wong, C.C.; Ng, E.K.W.; Yu, J. Molecular Alterations of Cancer Cell and Tumour Microenvironment in Metastatic Gastric Cancer. Oncogene 2018, 37, 4903–4920. [Google Scholar] [CrossRef] [PubMed]
  3. Wu, S.-M.; Lin, W.-Y.; Shen, C.-C.; Pan, H.-C.; Keh-Bin, W.; Chen, Y.-C.; Jan, Y.-J.; Lai, D.-W.; Tang, S.-C.; Tien, H.-R.; et al. Melatonin Set out to ER Stress Signaling Thwarts Epithelial Mesenchymal Transition and Peritoneal Dissemination via Calpain-Mediated C/EBPβ and NFκB Cleavage. J. Pineal Res. 2016, 60, 142–154. [Google Scholar] [CrossRef] [PubMed]
  4. Huang, J.; Xiao, D.; Li, G.; Ma, J.; Chen, P.; Yuan, W.; Hou, F.; Ge, J.; Zhong, M.; Tang, Y.; et al. EphA2 Promotes Epithelial-Mesenchymal Transition through the Wnt/β-Catenin Pathway in Gastric Cancer Cells. Oncogene 2014, 33, 2737–2747. [Google Scholar] [CrossRef] [Green Version]
  5. Baghban, R.; Roshangar, L.; Jahanban-Esfahlan, R.; Seidi, K.; Ebrahimi-Kalan, A.; Jaymand, M.; Kolahian, S.; Javaheri, T.; Zare, P. Tumor Microenvironment Complexity and Therapeutic Implications at a Glance. Cell Commun. Signal. 2020, 18, 59. [Google Scholar] [CrossRef] [Green Version]
  6. Oliver, A.J.; Lau, P.K.H.; Unsworth, A.S.; Loi, S.; Darcy, P.K.; Kershaw, M.H.; Slaney, C.Y. Tissue-Dependent Tumor Microenvironments and Their Impact on Immunotherapy Responses. Front. Immunol. 2018, 9, 70. [Google Scholar] [CrossRef] [Green Version]
  7. Hirata, E.; Sahai, E. Tumor Microenvironment and Differential Responses to Therapy. Cold Spring Harb. Perspect Med. 2017, 7, a026781. [Google Scholar] [CrossRef] [Green Version]
  8. Balkwill, F.R.; Capasso, M.; Hagemann, T. The Tumor Microenvironment at a Glance. J. Cell Sci. 2012, 125, 5591–5596. [Google Scholar] [CrossRef] [Green Version]
  9. Bagchi, S.; Yuan, R.; Engleman, E.G. Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance. Annu. Rev. Pathol. 2021, 16, 223–249. [Google Scholar] [CrossRef]
  10. Tavora, B.; Reynolds, L.E.; Batista, S.; Demircioglu, F.; Fernandez, I.; Lechertier, T.; Lees, D.M.; Wong, P.-P.; Alexopoulou, A.; Elia, G.; et al. Endothelial-Cell FAK Targeting Sensitizes Tumours to DNA-Damaging Therapy. Nature 2014, 514, 112–116. [Google Scholar] [CrossRef] [Green Version]
  11. Battram, A.M.; Bachiller, M.; Martín-Antonio, B. Senescence in the Development and Response to Cancer with Immunotherapy: A Double-Edged Sword. Int. J. Mol. Sci. 2020, 21, 4346. [Google Scholar] [CrossRef]
  12. Bent, E.H.; Gilbert, L.A.; Hemann, M.T. A Senescence Secretory Switch Mediated by PI3K/AKT/MTOR Activation Controls Chemoprotective Endothelial Secretory Responses. Genes Dev. 2016, 30, 1811–1821. [Google Scholar] [CrossRef] [Green Version]
  13. Jeong, S.K.; Kim, J.S.; Lee, C.G.; Park, Y.-S.; Kim, S.D.; Yoon, S.O.; Han, D.H.; Lee, K.Y.; Jeong, M.H.; Jo, W.S. Tumor Associated Macrophages Provide the Survival Resistance of Tumor Cells to Hypoxic Microenvironmental Condition through IL-6 Receptor-Mediated Signals. Immunobiology 2017, 222, 55–65. [Google Scholar] [CrossRef]
  14. Shree, T.; Olson, O.C.; Elie, B.T.; Kester, J.C.; Garfall, A.L.; Simpson, K.; Bell-McGuinn, K.M.; Zabor, E.C.; Brogi, E.; Joyce, J.A. Macrophages and Cathepsin Proteases Blunt Chemotherapeutic Response in Breast Cancer. Genes Dev. 2011, 25, 2465–2479. [Google Scholar] [CrossRef] [Green Version]
  15. Dijkgraaf, E.M.; Heusinkveld, M.; Tummers, B.; Vogelpoel, L.T.C.; Goedemans, R.; Jha, V.; Nortier, J.W.R.; Welters, M.J.P.; Kroep, J.R.; van der Burg, S.H. Chemotherapy Alters Monocyte Differentiation to Favor Generation of Cancer-Supporting M2 Macrophages in the Tumor Microenvironment. Cancer Res. 2013, 73, 2480–2492. [Google Scholar] [CrossRef] [Green Version]
  16. Wang, Z.; Tang, Y.; Tan, Y.; Wei, Q.; Yu, W. Cancer-Associated Fibroblasts in Radiotherapy: Challenges and New Opportunities. Cell Commun. Signal 2019, 17, 47. [Google Scholar] [CrossRef] [Green Version]
  17. Tommelein, J.; De Vlieghere, E.; Verset, L.; Melsens, E.; Leenders, J.; Descamps, B.; Debucquoy, A.; Vanhove, C.; Pauwels, P.; Gespach, C.P.; et al. Radiotherapy-Activated Cancer-Associated Fibroblasts Promote Tumor Progression through Paracrine IGF1R Activation. Cancer Res. 2018, 78, 659–670. [Google Scholar] [CrossRef] [Green Version]
  18. Wen, S.; Hou, Y.; Fu, L.; Xi, L.; Yang, D.; Zhao, M.; Qin, Y.; Sun, K.; Teng, Y.; Liu, M. Cancer-Associated Fibroblast (CAF)-Derived IL32 Promotes Breast Cancer Cell Invasion and Metastasis via Integrin Β3-P38 MAPK Signalling. Cancer Lett. 2019, 442, 320–332. [Google Scholar] [CrossRef]
  19. Özdemir, B.C.; Pentcheva-Hoang, T.; Carstens, J.L.; Zheng, X.; Wu, C.-C.; Simpson, T.R.; Laklai, H.; Sugimoto, H.; Kahlert, C.; Novitskiy, S.V.; et al. Depletion of Carcinoma-Associated Fibroblasts and Fibrosis Induces Immunosuppression and Accelerates Pancreas Cancer with Reduced Survival. Cancer Cell 2014, 25, 719–734. [Google Scholar] [CrossRef] [Green Version]
  20. Bui, J.D.; Schreiber, R.D. Cancer Immunosurveillance, Immunoediting and Inflammation: Independent or Interdependent Processes? Curr. Opin. Immunol. 2007, 19, 203–208. [Google Scholar] [CrossRef]
  21. Gupta, A.; Probst, H.C.; Vuong, V.; Landshammer, A.; Muth, S.; Yagita, H.; Schwendener, R.; Pruschy, M.; Knuth, A.; van den Broek, M. Radiotherapy Promotes Tumor-Specific Effector CD8+ T Cells via Dendritic Cell Activation. J. Immunol. 2012, 189, 558–566. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Maude, S.L.; Laetsch, T.W.; Buechner, J.; Rives, S.; Boyer, M.; Bittencourt, H.; Bader, P.; Verneris, M.R.; Stefanski, H.E.; Myers, G.D.; et al. Tisagenlecleucel in Children and Young Adults with B-Cell Lymphoblastic Leukemia. N. Engl. J. Med. 2018, 378, 439–448. [Google Scholar] [CrossRef] [PubMed]
  23. Ortíz-Maldonado, V.; Rives, S.; Castellà, M.; Alonso-Saladrigues, A.; Benítez-Ribas, D.; Caballero-Baños, M.; Baumann, T.; Cid, J.; Garcia-Rey, E.; Llanos, C.; et al. CART19-BE-01: A Multicenter Trial of ARI-0001 Cell Therapy in Patients with CD19+ Relapsed/Refractory Malignancies. Mol. Ther. 2021, 29, 636–644. [Google Scholar] [CrossRef] [PubMed]
  24. Perez-Amill, L.; Suñe, G.; Antoñana-Vildosola, A.; Castella, M.; Najjar, A.; Bonet, J.; Fernández-Fuentes, N.; Inogés, S.; López, A.; Bueno, C.; et al. Preclinical Development of a Humanized Chimeric Antigen Receptor against B Cell Maturation Antigen for Multiple Myeloma. Haematologica 2021, 106, 173–184. [Google Scholar] [CrossRef] [Green Version]
  25. Castella, M.; Fernández de Larrea, C.; Martín-Antonio, B. Immunotherapy: A Novel Era of Promising Treatments for Multiple Myeloma. Int. J. Mol. Sci. 2018, 19, 3613. [Google Scholar] [CrossRef] [Green Version]
  26. Martinez, M.; Moon, E.K. CAR T Cells for Solid Tumors: New Strategies for Finding, Infiltrating, and Surviving in the Tumor Microenvironment. Front. Immunol. 2019, 10, 128. [Google Scholar] [CrossRef] [Green Version]
  27. Raje, N.; Berdeja, J.; Lin, Y.; Siegel, D.; Jagannath, S.; Madduri, D.; Liedtke, M.; Rosenblatt, J.; Maus, M.V.; Turka, A.; et al. Anti-BCMA CAR T-Cell Therapy Bb2121 in Relapsed or Refractory Multiple Myeloma. N. Engl. J. Med. 2019, 380, 1726–1737. [Google Scholar] [CrossRef]
  28. García-Ortiz, A.; Rodríguez-García, Y.; Encinas, J.; Maroto-Martín, E.; Castellano, E.; Teixidó, J.; Martínez-López, J. The Role of Tumor Microenvironment in Multiple Myeloma Development and Progression. Cancers 2021, 13, 217. [Google Scholar] [CrossRef]
  29. Kumar, S.K.; Rajkumar, V.; Kyle, R.A.; van Duin, M.; Sonneveld, P.; Mateos, M.-V.; Gay, F.; Anderson, K.C. Multiple Myeloma. Nat. Rev. Dis. Primers. 2017, 3, 17046. [Google Scholar] [CrossRef]
  30. Bone Marrow Niches in Haematological Malignancies | Nature Reviews Cancer. Available online: https://www.nature.com/articles/s41568-020-0245-2 (accessed on 20 June 2022).
  31. Glavey, S.V.; Naba, A.; Manier, S.; Clauser, K.; Tahri, S.; Park, J.; Reagan, M.R.; Moschetta, M.; Mishima, Y.; Gambella, M.; et al. Proteomic Characterization of Human Multiple Myeloma Bone Marrow Extracellular Matrix. Leukemia 2017, 31, 2426–2434. [Google Scholar] [CrossRef]
  32. Landowski, T.H.; Olashaw, N.E.; Agrawal, D.; Dalton, W.S. Cell Adhesion-Mediated Drug Resistance (CAM-DR) Is Associated with Activation of NF-ΚB (RelB/P50) in Myeloma Cells. Oncogene 2003, 22, 2417–2421. [Google Scholar] [CrossRef] [Green Version]
  33. Targeting the Bone Marrow Microenvironment in Multiple Myeloma-Kawano-2015-Immunological Review-Wiley Online Library. Available online: https://onlinelibrary.wiley.com/doi/10.1111/imr.12233 (accessed on 23 May 2022).
  34. Kouroukis, T.C.; Baldassarre, F.G.; Haynes, A.E.; Imrie, K.; Reece, D.E.; Cheung, M.C. Bortezomib in Multiple Myeloma: Systematic Review and Clinical Considerations. Curr. Oncol. 2014, 21, 573–603. [Google Scholar] [CrossRef] [Green Version]
  35. Ghobrial, I.M.; Liu, C.-J.; Zavidij, O.; Azab, A.K.; Baz, R.; Laubach, J.P.; Mishima, Y.; Armand, P.; Munshi, N.C.; Basile, F.; et al. Phase I/II Trial of the CXCR4 Inhibitor Plerixafor in Combination with Bortezomib as a Chemosensitization Strategy in Relapsed/Refractory Multiple Myeloma. Am. J. Hematol. 2019, 94, 1244–1253. [Google Scholar] [CrossRef]
  36. Ghobrial, I.M. Myeloma as a Model for the Process of Metastasis: Implications for Therapy. Blood 2012, 120, 20–30. [Google Scholar] [CrossRef] [Green Version]
  37. Méndez-Ferrer, S.; Michurina, T.V.; Ferraro, F.; Mazloom, A.R.; MacArthur, B.D.; Lira, S.A.; Scadden, D.T.; Ma’ayan, A.; Enikolopov, G.N.; Frenette, P.S. Mesenchymal and Haematopoietic Stem Cells Form a Unique Bone Marrow Niche. Nature 2010, 466, 829–834. [Google Scholar] [CrossRef]
  38. Dazzi, F.; Ramasamy, R.; Glennie, S.; Jones, S.P.; Roberts, I. The Role of Mesenchymal Stem Cells in Haemopoiesis. Blood Rev. 2006, 20, 161–171. [Google Scholar] [CrossRef]
  39. Hideshima, T.; Mitsiades, C.; Tonon, G.; Richardson, P.G.; Anderson, K.C. Understanding Multiple Myeloma Pathogenesis in the Bone Marrow to Identify New Therapeutic Targets. Nat. Rev. Cancer 2007, 7, 585–598. [Google Scholar] [CrossRef]
  40. Asosingh, K.; Vankerkhove, V.; Riet, I.V.; Camp, B.V.; Vanderkerken, K. Selective in Vivo Growth of Lymphocyte Function- Associated Antigen-1–Positive Murine Myeloma Cells: Involvement of Function-Associated Antigen-1–Mediated Homotypic Cell-Cell Adhesion. Exp. Hematol. 2003, 31, 48–55. [Google Scholar] [CrossRef]
  41. Schmidmaier, R.; Mandl-Weber, S.; Gaul, L.; Baumann, P.; Bumeder, I.; Straka, C.; Emmerich, B. Inhibition of Lymphocyte Function Associated Antigen 1 by LFA878 Induces Apoptosis in Multiple Myeloma Cells and Is Associated with Downregulation of the Focal Adhesion Kinase/Phosphatidylinositol 3 Kinase/Akt Pathway. Int. J. Oncol. 2007, 31, 969–976. [Google Scholar] [CrossRef] [Green Version]
  42. Harmer, D.; Falank, C.; Reagan, M.R. Interleukin-6 Interweaves the Bone Marrow Microenvironment, Bone Loss, and Multiple Myeloma. Front. Endocrinol. 2019, 9, 788. [Google Scholar] [CrossRef] [Green Version]
  43. Hideshima, T.; Bergsagel, P.L.; Kuehl, W.M.; Anderson, K.C. Advances in Biology of Multiple Myeloma: Clinical Applications. Blood 2004, 104, 607–618. [Google Scholar] [CrossRef] [Green Version]
  44. Orlowski, R.Z.; Gercheva, L.; Williams, C.; Sutherland, H.; Robak, T.; Masszi, T.; Goranova-Marinova, V.; Dimopoulos, M.A.; Cavenagh, J.D.; Špička, I.; et al. A Phase 2, Randomized, Double-Blind, Placebo-Controlled Study of Siltuximab (Anti-IL-6 MAb) and Bortezomib versus Bortezomib Alone in Patients with Relapsed or Refractory Multiple Myeloma. Am. J. Hematol. 2015, 90, 42–49. [Google Scholar] [CrossRef] [Green Version]
  45. Matsuyama, Y.; Nagashima, T.; Honne, K.; Kamata, Y.; Iwamoto, M.; Okazaki, H.; Sato, K.; Ozawa, K.; Minota, S. Successful Treatment of a Patient with Rheumatoid Arthritis and IgA-κ Multiple Myeloma with Tocilizumab. Intern. Med. 2011, 50, 639–642. [Google Scholar] [CrossRef] [Green Version]
  46. Corre, J.; Mahtouk, K.; Attal, M.; Gadelorge, M.; Huynh, A.; Fleury-Cappellesso, S.; Danho, C.; Laharrague, P.; Klein, B.; Rème, T.; et al. Bone Marrow Mesenchymal Stem Cells Are Abnormal in Multiple Myeloma. Leukemia 2007, 21, 1079–1088. [Google Scholar] [CrossRef] [PubMed]
  47. Zdzisińska, B.; Bojarska-Junak, A.; Dmoszyńska, A.; Kandefer-Szerszeń, M. Abnormal Cytokine Production by Bone Marrow Stromal Cells of Multiple Myeloma Patients in Response to RPMI8226 Myeloma Cells. Arch. Immunol. Ther. Exp. 2008, 56, 207. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Deng, M.; Yuan, H.; Peng, H.; Liu, S.; Xiao, X.; Wang, Z.; Zhang, G.; Xiao, H. Mesenchymal Stem Cells Inhibit the Effects of Dexamethasone in Multiple Myeloma Cells. Stem Cells Int. 2022, 2022, e4855517. [Google Scholar] [CrossRef] [PubMed]
  49. BAFF and APRIL Protect Myeloma Cells from Apoptosis Induced by Interleukin 6 Deprivation and Dexamethasone | Blood | American Society of Hematology. Available online: https://ashpublications.org/blood/article/103/8/3148/18054/BAFF-and-APRIL-protect-myeloma-cells-from (accessed on 23 May 2022).
  50. Expression of BCMA, TACI, and BAFF-R in Multiple Myeloma: A Mechanism for Growth and Survival | Blood | American Society of Hematology. Available online: https://ashpublications.org/blood/article/103/2/689/17829/Expression-of-BCMA-TACI-and-BAFF-R-in-multiple (accessed on 23 May 2022).
  51. APRIL and BCMA Promote Human Multiple Myeloma Growth and Immunosuppression in the Bone Marrow Microenvironment | Blood | American Society of Hematology. Available online: https://ashpublications.org/blood/article/127/25/3225/35206/APRIL-and-BCMA-promote-human-multiple-myeloma (accessed on 23 May 2022).
  52. Lee, L.; Draper, B.; Chaplin, N.; Philip, B.; Chin, M.; Galas-Filipowicz, D.; Onuoha, S.; Thomas, S.; Baldan, V.; Bughda, R.; et al. An APRIL-Based Chimeric Antigen Receptor for Dual Targeting of BCMA and TACI in Multiple Myeloma. Blood 2018, 131, 746–758. [Google Scholar] [CrossRef] [PubMed]
  53. Holthof, L.C.; van der Schans, J.J.; Katsarou, A.; Poels, R.; Gelderloos, A.T.; Drent, E.; van Hal-van Veen, S.E.; Li, F.; Zweegman, S.; van de Donk, N.W.C.J.; et al. Bone Marrow Mesenchymal Stromal Cells Can Render Multiple Myeloma Cells Resistant to Cytotoxic Machinery of CAR T Cells through Inhibition of Apoptosis. Clin. Cancer Res. 2021, 27, 3793–3803. [Google Scholar] [CrossRef]
  54. The Role of Tumor Necrosis Factor α in the Pathophysiology of Human Multiple Myeloma: Therapeutic Applications | Oncogene. Available online: https://www.nature.com/articles/1204623 (accessed on 23 May 2022).
  55. Tsubaki, M.; Komai, M.; Itoh, T.; Imano, M.; Sakamoto, K.; Shimaoka, H.; Ogawa, N.; Mashimo, K.; Fujiwara, D.; Takeda, T.; et al. Inhibition of the Tumour Necrosis Factor-Alpha Autocrine Loop Enhances the Sensitivity of Multiple Myeloma Cells to Anticancer Drugs. Eur. J. Cancer 2013, 49, 3708–3717. [Google Scholar] [CrossRef]
  56. Calip, G.S.; Lee, W.-J.; Lee, T.A.; Schumock, G.T.; Chiu, B.C.-H. Tumor Necrosis Factor-Alpha Inhibitor Medications for Inflammatory Conditions and Incidence of Multiple Myeloma. Blood 2015, 126, 2954. [Google Scholar] [CrossRef]
  57. Sebba, A. Tocilizumab: The First Interleukin-6-Receptor Inhibitor. Am. J. Health Syst. Pharm. 2008, 65, 1413–1418. [Google Scholar] [CrossRef]
  58. Iyer, S.P.; Beck, J.T.; Stewart, A.K.; Shah, J.; Kelly, K.R.; Isaacs, R.; Bilic, S.; Sen, S.; Munshi, N.C. A Phase IB Multicentre Dose-Determination Study of BHQ880 in Combination with Anti-Myeloma Therapy and Zoledronic Acid in Patients with Relapsed or Refractory Multiple Myeloma and Prior Skeletal-Related Events. Br. J. Haematol. 2014, 167, 366–375. [Google Scholar] [CrossRef]
  59. Raje, N.S.; Moreau, P.; Terpos, E.; Benboubker, L.; Grząśko, N.; Holstein, S.A.; Oriol, A.; Huang, S.-Y.; Beksac, M.; Kuliczkowski, K.; et al. Phase 2 Study of Tabalumab, a Human Anti-B-Cell Activating Factor Antibody, with Bortezomib and Dexamethasone in Patients with Previously Treated Multiple Myeloma. Br. J. Haematol. 2017, 176, 783–795. [Google Scholar] [CrossRef]
  60. Roodman, G.D. Osteoblast Function in Myeloma. Bone 2011, 48, 135–140. [Google Scholar] [CrossRef]
  61. Gau, Y.-C.; Yeh, T.-J.; Hsu, C.-M.; Hsiao, S.Y.; Hsiao, H.-H. Pathogenesis and Treatment of Myeloma-Related Bone Disease. Int. J. Mol. Sci. 2022, 23, 3112. [Google Scholar] [CrossRef]
  62. Valentin-Opran, A.; Charhon, S.A.; Meunier, P.J.; Edouard, C.M.; Arlot, M.E. Quantitative Histology of Myeloma-Induced Bone Changes. Br. J. Haematol. 1982, 52, 601–610. [Google Scholar] [CrossRef]
  63. Choi, S.J.; Oba, Y.; Gazitt, Y.; Alsina, M.; Cruz, J.; Anderson, J.; Roodman, G.D. Antisense Inhibition of Macrophage Inflammatory Protein 1-α Blocks Bone Destruction in a Model of Myeloma Bone Disease. J. Clin. Investig. 2001, 108, 1833–1841. [Google Scholar] [CrossRef]
  64. Abe, M.; Hiura, K.; Wilde, J.; Moriyama, K.; Hashimoto, T.; Ozaki, S.; Wakatsuki, S.; Kosaka, M.; Kido, S.; Inoue, D.; et al. Role for Macrophage Inflammatory Protein (MIP)-1alpha and MIP-1beta in the Development of Osteolytic Lesions in Multiple Myeloma. Blood 2002, 100, 2195–2202. [Google Scholar] [CrossRef]
  65. Macrophage Inflammatory Protein-1α Is an Osteoclastogenic Factor in Myeloma That Is Independent of Receptor Activator of Nuclear Factor ΚB Ligand | Blood | American Society of Hematology. Available online: https://ashpublications.org/blood/article/97/11/3349/107426/Macrophage-inflammatory-protein-1-is-an (accessed on 23 May 2022).
  66. Notch-Directed Microenvironment Reprogramming in Myeloma: A Single Path to Multiple Outcomes | Leukemia. Available online: https://www.nature.com/articles/leu20136 (accessed on 23 May 2022).
  67. Boyce, B.F.; Xing, L. Functions of RANKL/RANK/OPG in Bone Modeling and Remodeling. Arch. Biochem. Biophys. 2008, 473, 139–146. [Google Scholar] [CrossRef] [Green Version]
  68. Michigami, T.; Shimizu, N.; Williams, P.J.; Niewolna, M.; Dallas, S.L.; Mundy, G.R.; Yoneda, T. Cell-Cell Contact between Marrow Stromal Cells and Myeloma Cells via VCAM-1 and Alpha (4) Beta (1)-Integrin Enhances Production of Osteoclast-Stimulating Activity. Blood 2000, 96, 1953–1960. [Google Scholar] [CrossRef]
  69. Terpos, E.; Raje, N.; Croucher, P.; Garcia-Sanz, R.; Leleu, X.; Pasteiner, W.; Wang, Y.; Glennane, A.; Canon, J.; Pawlyn, C. Denosumab Compared with Zoledronic Acid on PFS in Multiple Myeloma: Exploratory Results of an International Phase 3 Study. Blood Adv. 2021, 5, 725–736. [Google Scholar] [CrossRef]
  70. Huang, S.-Y.; Yoon, S.-S.; Shimizu, K.; Chng, W.J.; Chang, C.-S.; Wong, R.S.-M.; Gao, S.; Wang, Y.; Gordon, S.W.; Glennane, A.; et al. Denosumab Versus Zoledronic Acid in Bone Disease Treatment of Newly Diagnosed Multiple Myeloma: An International, Double-Blind, Randomized Controlled Phase 3 Study—Asian Subgroup Analysis. Adv. Ther. 2020, 37, 3404–3416. [Google Scholar] [CrossRef]
  71. Hanley, D.A.; Adachi, J.D.; Bell, A.; Brown, V. Denosumab: Mechanism of Action and Clinical Outcomes. Int. J. Clin. Pract. 2012, 66, 1139–1146. [Google Scholar] [CrossRef] [Green Version]
  72. Myeloma Cells Block RUNX2/CBFA1 Activity in Human Bone Marrow Osteoblast Progenitors and Inhibit Osteoblast Formation and Differentiation | Blood | American Society of Hematology. Available online: https://ashpublications.org/blood/article/106/7/2472/21687/Myeloma-cells-block-RUNX2-CBFA1-activity-in-human (accessed on 23 May 2022).
  73. Osteoprotegerin Is Bound, Internalized, and Degraded by Multiple Myeloma Cells | Blood | American Society of Hematology. Available online: https://ashpublications.org/blood/article/100/8/3002/106454/Osteoprotegerin-is-bound-internalized-and-degraded (accessed on 23 May 2022).
  74. Mori, Y.; Shimizu, N.; Dallas, M.; Niewolna, M.; Story, B.; Williams, P.J.; Mundy, G.R.; Yoneda, T. Anti-A4 Integrin Antibody Suppresses the Development of Multiple Myeloma and Associated Osteoclastic Osteolysis. Blood 2004, 104, 2149–2154. [Google Scholar] [CrossRef]
  75. Padmanabhan, S.; Beck, J.T.; Kelly, K.R.; Munshi, N.C.; Dzik-Jurasz, A.; Gangolli, E.; Ettenberg, S.; Miner, K.; Bilic, S.; Whyte, W.; et al. A Phase I/II Study of BHQ880, a Novel Osteoblat Activating, Anti-DKK1 Human Monoclonal Antibody, in Relapsed and Refractory Multiple Myeloma (MM) Patients Treated with Zoledronic Acid (Zol) and Anti-Myeloma Therapy (MM Tx). Blood 2009, 114, 750. [Google Scholar] [CrossRef]
  76. Vacca, A.; Ria, R.; Reale, A.; Ribatti, D. Angiogenesis in Multiple Myeloma. Angiogenes. Lymphangiogenes. Clin. Implic. 2014, 99, 180–196. [Google Scholar] [CrossRef]
  77. Ribatti, D.; Nico, B.; Vacca, A. Multiple Myeloma as a Model for the Role of Bone Marrow Niches in the Control of Angiogenesis. Int. Rev. Cell Mol. Biol. 2015, 314, 259–282. [Google Scholar] [CrossRef]
  78. Mondello, P.; Cuzzocrea, S.; Navarra, M.; Mian, M. Bone Marrow Micro-Environment Is a Crucial Player for Myelomagenesis and Disease Progression. Oncotarget 2017, 8, 20394–20409. [Google Scholar] [CrossRef] [Green Version]
  79. Hanahan, D.; Weinberg, R.A. Hallmarks of Cancer: The next Generation. Cell 2011, 144, 646–674. [Google Scholar] [CrossRef] [Green Version]
  80. Rajkumar, S.V.; Mesa, R.A.; Fonseca, R.; Schroeder, G.; Plevak, M.F.; Dispenzieri, A.; Lacy, M.Q.; Lust, J.A.; Witzig, T.E.; Gertz, M.A.; et al. Bone Marrow Angiogenesis in 400 Patients with Monoclonal Gammopathy of Undetermined Significance, Multiple Myeloma, and Primary Amyloidosis. Clin. Cancer Res. 2002, 8, 2210–2216. [Google Scholar]
  81. Bhaskar, A.; Tiwary, B.N. Hypoxia Inducible Factor-1 Alpha and Multiple Myeloma. Int. J. Adv. Res. 2016, 4, 706–715. [Google Scholar]
  82. Angiogenic Switch during 5T2MM Murine Myeloma Tumorigenesis: Role of CD45 Heterogeneity | Blood | American Society of Hematology. Available online: https://ashpublications.org/blood/article/103/8/3131/18020/Angiogenic-switch-during-5T2MM-murine-myeloma (accessed on 24 May 2022).
  83. Ria, R.; Todoerti, K.; Berardi, S.; Coluccia, A.M.L.; De Luisi, A.; Mattioli, M.; Ronchetti, D.; Morabito, F.; Guarini, A.; Petrucci, M.T.; et al. Gene Expression Profiling of Bone Marrow Endothelial Cells in Patients with Multiple Myeloma. Clin. Cancer Res. 2009, 15, 5369–5378. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  84. Solimando, A.G.; Summa, S.D.; Vacca, A.; Ribatti, D. Cancer-Associated Angiogenesis: The Endothelial Cell as a Checkpoint for Immunological Patrolling. Cancers 2020, 12, 3380. [Google Scholar] [CrossRef] [PubMed]
  85. Ribatti, D.; Vacca, A.; Nico, B.; Roncali, L.; Dammacco, F. Postnatal Vasculogenesis. Mech. Dev. 2001, 100, 157–163. [Google Scholar] [CrossRef]
  86. Moschetta, M.; Mishima, Y.; Kawano, Y.; Manier, S.; Paiva, B.; Palomera, L.; Aljawai, Y.; Calcinotto, A.; Unitt, C.; Sahin, I.; et al. Targeting Vasculogenesis to Prevent Progression in Multiple Myeloma. Leukemia 2016, 30, 1103–1115. [Google Scholar] [CrossRef] [PubMed]
  87. Tenreiro, M.M.; Correia, M.L.; Brito, M.A. Endothelial Progenitor Cells in Multiple Myeloma Neovascularization: A Brick to the Wall. Angiogenesis 2017, 20, 443–462. [Google Scholar] [CrossRef]
  88. Reale, A.; Melaccio, A.; Lamanuzzi, A.; Saltarella, I.; Dammacco, F.; Vacca, A.; Ria, R. Functional and Biological Role of Endothelial Precursor Cells in Tumour Progression: A New Potential Therapeutic Target in Haematological Malignancies. Stem. Cells Int. 2015, 2016, e7954580. [Google Scholar] [CrossRef] [Green Version]
  89. Sweeney, M.; Foldes, G. It Takes Two: Endothelial-Perivascular Cell Cross-Talk in Vascular Development and Disease. Front. Cardiovasc. Med. 2018, 5, 154. [Google Scholar] [CrossRef]
  90. Dankbar, B.; Padró, T.; Leo, R.; Feldmann, B.; Kropff, M.; Mesters, R.M.; Serve, H.; Berdel, W.E.; Kienast, J. Vascular Endothelial Growth Factor and Interleukin-6 in Paracrine Tumor-Stromal Cell Interactions in Multiple Myeloma. Blood 2000, 95, 2630–2636. [Google Scholar] [CrossRef]
  91. Ria, R.; Melaccio, A.; Racanelli, V.; Vacca, A. Anti-VEGF Drugs in the Treatment of Multiple Myeloma Patients. J. Clin. Med. 2020, 9, 1765. [Google Scholar] [CrossRef]
  92. Somlo, G.; Lashkari, A.; Bellamy, W.; Zimmerman, T.M.; Tuscano, J.M.; O’Donnell, M.R.; Mohrbacher, A.F.; Forman, S.J.; Frankel, P.; Chen, H.X.; et al. Phase II Randomized Trial of Bevacizumab versus Bevacizumab and Thalidomide for Relapsed/Refractory Multiple Myeloma: A California Cancer Consortium Trial. Br. J. Haematol. 2011, 154, 533–535. [Google Scholar] [CrossRef] [Green Version]
  93. White, D.; Kassim, A.; Bhaskar, B.; Yi, J.; Wamstad, K.; Paton, V.E. Results from AMBER, a Randomized Phase 2 Study of Bevacizumab and Bortezomib versus Bortezomib in Relapsed or Refractory Multiple Myeloma. Cancer 2013, 119, 339–347. [Google Scholar] [CrossRef]
  94. Yordanova, A.; Hose, D.; Neben, K.; Witzens-Harig, M.; Gütgemann, I.; Raab, M.-S.; Moehler, T.; Goldschmidt, H.; Schmidt-Wolf, I.G. Sorafenib in Patients with Refractory or Recurrent Multiple Myeloma. Hematol. Oncol. 2013, 31, 197–200. [Google Scholar] [CrossRef]
  95. Srkalovic, G.; Hussein, M.A.; Hoering, A.; Zonder, J.A.; Popplewell, L.L.; Trivedi, H.; Mazzoni, S.; Sexton, R.; Orlowski, R.Z.; Barlogie, B. A Phase II Trial of BAY 43-9006 (Sorafenib) (NSC-724772) in Patients with Relapsing and Resistant Multiple Myeloma: SWOG S0434. Cancer Med. 2014, 3, 1275–1283. [Google Scholar] [CrossRef]
  96. Kumar, S.; Witzig, T.E.; Dispenzieri, A.; Lacy, M.Q.; Wellik, L.E.; Fonseca, R.; Lust, J.A.; Gertz, M.A.; Kyle, R.A.; Greipp, P.R.; et al. Effect of Thalidomide Therapy on Bone Marrow Angiogenesis in Multiple Myeloma. Leukemia 2004, 18, 624–627. [Google Scholar] [CrossRef] [Green Version]
  97. Terpos, E.; Katodritou, E.; Symeonidis, A.; Zagouri, F.; Gerofotis, A.; Christopoulou, G.; Gavriatopoulou, M.; Christoulas, D.; Ntanasis-Stathopoulos, I.; Kourakli, A.; et al. Effect of Induction Therapy with Lenalidomide, Doxorubicin and Dexamethasone on Bone Remodeling and Angiogenesis in Newly Diagnosed Multiple Myeloma. Int. J. Cancer 2019, 145, 559–568. [Google Scholar] [CrossRef]
  98. Deng, M.; Yuan, H.; Liu, S.; Hu, Z.; Xiao, H. Exosome-Transmitted LINC00461 Promotes Multiple Myeloma Cell Proliferation and Suppresses Apoptosis by Modulating MicroRNA/BCL-2 Expression. Cytotherapy 2019, 21, 96–106. [Google Scholar] [CrossRef]
  99. Scavelli, C.; Di Pietro, G.; Cirulli, T.; Coluccia, M.; Boccarelli, A.; Giannini, T.; Mangialardi, G.; Bertieri, R.; Coluccia, A.M.L.; Ribatti, D.; et al. Zoledronic Acid Affects Over-Angiogenic Phenotype of Endothelial Cells in Patients with Multiple Myeloma. Mol. Cancer Ther. 2007, 6, 3256–3262. [Google Scholar] [CrossRef] [Green Version]
  100. Guillerey, C.; Harjunpää, H.; Carrié, N.; Kassem, S.; Teo, T.; Miles, K.; Krumeich, S.; Weulersse, M.; Cuisinier, M.; Stannard, K.; et al. TIGIT Immune Checkpoint Blockade Restores CD8+ T-Cell Immunity against Multiple Myeloma. Blood 2018, 132, 1689–1694. [Google Scholar] [CrossRef] [Green Version]
  101. Noonan, K.A.; Huff, C.A.; Davis, J.; Lemas, M.V.; Fiorino, S.; Bitzan, J.; Ferguson, A.; Emerling, A.; Luznik, L.; Matsui, W.; et al. Adoptive Transfer of Activated Marrow-Infiltrating Lymphocytes Induces Measurable Antitumor Immunity in the Bone Marrow in Multiple Myeloma. Sci. Transl. Med. 2015, 7, 288ra78. [Google Scholar] [CrossRef] [Green Version]
  102. Teijeira, A.; Garasa, S.; Etxeberria, I.; Gato-Cañas, M.; Melero, I.; Delgoffe, G.M. Metabolic Consequences of T-Cell Costimulation in Anticancer Immunity. Cancer Immunol. Res. 2019, 7, 1564–1569. [Google Scholar] [CrossRef]
  103. Wherry, E.J. T Cell Exhaustion. Nat. Immunol. 2011, 12, 492–499. [Google Scholar] [CrossRef]
  104. Arai, Y.; Choi, U.; Corsino, C.I.; Koontz, S.M.; Tajima, M.; Sweeney, C.L.; Black, M.A.; Feldman, S.A.; Dinauer, M.C.; Malech, H.L. Enhanced Expression of CXCR4 Facilitates C-Kit-Targeted CAR-T Cell Trafficking to Bone Marrow and Enables Donor Stem Cell Engraftment. Biol. Blood Marrow Transplant. 2018, 24, S311. [Google Scholar] [CrossRef]
  105. Alsina, M.; Shah, N.; Raje, N.S.; Jagannath, S.; Madduri, D.; Kaufman, J.L.; Berdeja, J.G. Updated Results from the Phase I CRB-402 Study of Anti-Bcma CAR-T Cell Therapy Bb21217 in Patients with Relapsed and Refractory Multiple Myeloma: Correlation of Expansion and Duration of Response with T Cell Phenotypes. Blood 2020, 136, 25–26. [Google Scholar] [CrossRef]
  106. Le Calvez, B.; Moreau, P.; Touzeau, C. Immune Checkpoint Inhibitors for the Treatment of Myeloma: Novel Investigational Options. Expert Opin. Investig. Drugs 2021, 30, 965–973. [Google Scholar] [CrossRef]
  107. Ogawara, H.; Handa, H.; Yamazaki, T.; Toda, T.; Yoshida, K.; Nishimoto, N.; Al-ma’Quol, W.H.S.; Kaneko, Y.; Matsushima, T.; Tsukamoto, N.; et al. High Th1/Th2 Ratio in Patients with Multiple Myeloma. Leuk. Res. 2005, 29, 135–140. [Google Scholar] [CrossRef]
  108. Frassanito, M.A.; Cusmai, A.; Dammacco, F. Deregulated Cytokine Network and Defective Th1 Immune Response in Multiple Myeloma. Clin. Exp. Immunol. 2001, 125, 190–197. [Google Scholar] [CrossRef] [PubMed]
  109. Verkleij, C.P.M.; Broekmans, M.E.C.; van Duin, M.; Frerichs, K.A.; Kuiper, R.; de Jonge, A.V.; Kaiser, M.; Morgan, G.; Axel, A.; Boominathan, R.; et al. Preclinical Activity and Determinants of Response of the GPRC5DxCD3 Bispecific Antibody Talquetamab in Multiple Myeloma. Blood Adv. 2021, 5, 2196–2215. [Google Scholar] [CrossRef] [PubMed]
  110. Green, D.J.; Pont, M.; Sather, B.D.; Cowan, A.J.; Turtle, C.J.; Till, B.G.; Nagengast, A.M.; Libby, E.N., III; Becker, P.S.; Coffey, D.G.; et al. Fully Human Bcma Targeted Chimeric Antigen Receptor T Cells Administered in a Defined Composition Demonstrate Potency at Low Doses in Advanced Stage High Risk Multiple Myeloma. Blood 2018, 132, 1011. [Google Scholar] [CrossRef]
  111. Garfall, A.L.; Dancy, E.K.; Cohen, A.D.; Hwang, W.-T.; Fraietta, J.A.; Davis, M.M.; Levine, B.L.; Siegel, D.L.; Stadtmauer, E.A.; Vogl, D.T.; et al. T-Cell Phenotypes Associated with Effective CAR T-Cell Therapy in Postinduction vs Relapsed Multiple Myeloma. Blood Adv. 2019, 3, 2812–2815. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  112. Giannopoulos, K.; Kaminska, W.; Hus, I.; Dmoszynska, A. The Frequency of T Regulatory Cells Modulates the Survival of Multiple Myeloma Patients: Detailed Characterisation of Immune Status in Multiple Myeloma. Br. J. Cancer 2012, 106, 546–552. [Google Scholar] [CrossRef]
  113. Alrasheed, N.; Lee, L.; Ghorani, E.; Henry, J.Y.; Conde, L.; Chin, M.; Galas-Filipowicz, D.; Furness, A.J.S.; Chavda, S.J.; Richards, H.; et al. Marrow-Infiltrating Regulatory T Cells Correlate with the Presence of Dysfunctional CD4+PD-1+ Cells and Inferior Survival in Patients with Newly Diagnosed Multiple Myeloma. Clin. Cancer Res. 2020, 26, 3443–3454. [Google Scholar] [CrossRef] [Green Version]
  114. Feyler, S.; Scott, G.B.; Parrish, C.; Jarmin, S.; Evans, P.; Short, M.; McKinley, K.; Selby, P.J.; Cook, G. Tumour Cell Generation of Inducible Regulatory T-Cells in Multiple Myeloma Is Contact-Dependent and Antigen-Presenting Cell-Independent. PLoS ONE 2012, 7, e35981. [Google Scholar] [CrossRef] [Green Version]
  115. Takeuchi, Y.; Nishikawa, H. Roles of Regulatory T Cells in Cancer Immunity. Int. Immunol. 2016, 28, 401–409. [Google Scholar] [CrossRef] [Green Version]
  116. Braga, W.M.T.; da Silva, B.R.; de Carvalho, A.C.; Maekawa, Y.H.; Bortoluzzo, A.B.; Rizzatti, E.G.; Atanackovic, D.; Colleoni, G.W.B. FOXP3 and CTLA4 Overexpression in Multiple Myeloma Bone Marrow as a Sign of Accumulation of CD4+ T Regulatory Cells. Cancer Immunol. Immunother. 2014, 63, 1189–1197. [Google Scholar] [CrossRef] [Green Version]
  117. Dahlhoff, J.; Manz, H.; Steinfatt, T.; Delgado-Tascon, J.; Seebacher, E.; Schneider, T.; Wilnit, A.; Mokhtari, Z.; Tabares, P.; Böckle, D.; et al. Transient Regulatory T-Cell Targeting Triggers Immune Control of Multiple Myeloma and Prevents Disease Progression. Leukemia 2022, 36, 790–800. [Google Scholar] [CrossRef]
  118. Zhou, L.; Ivanov, I.I.; Spolski, R.; Min, R.; Shenderov, K.; Egawa, T.; Levy, D.E.; Leonard, W.J.; Littman, D.R. IL-6 Programs TH-17 Cell Differentiation by Promoting Sequential Engagement of the IL-21 and IL-23 Pathways. Nat. Immunol. 2007, 8, 967–974. [Google Scholar] [CrossRef]
  119. Prabhala, R.H.; Pelluru, D.; Fulciniti, M.; Prabhala, H.K.; Nanjappa, P.; Song, W.; Pai, C.; Amin, S.; Tai, Y.-T.; Richardson, P.G.; et al. Elevated IL-17 Produced by TH17 Cells Promotes Myeloma Cell Growth and Inhibits Immune Function in Multiple Myeloma. Blood 2010, 115, 5385–5392. [Google Scholar] [CrossRef]
  120. Lei, L.; Sun, J.; Han, J.; Jiang, X.; Wang, Z.; Chen, L. Interleukin-17 Induces Pyroptosis in Osteoblasts through the NLRP3 Inflammasome Pathway in Vitro. Int. Immunopharmacol. 2021, 96, 107781. [Google Scholar] [CrossRef]
  121. Zhao, L.-J.; Gao, S.; Li, X. Effects of Thalidomide on the Ratio of Th17 to Treg Cells in Peripheral Blood and Expression of IL-17 and IL-35 in Patients with Multiple Myeloma. Zhongguo Shi Yan Xue Ye Xue Za Zhi 2018, 26, 187–191. [Google Scholar] [CrossRef]
  122. Prabhala, R.H.; Fulciniti, M.; Pelluru, D.; Rashid, N.; Nigroiu, A.; Nanjappa, P.; Pai, C.; Lee, S.; Prabhala, N.S.; Bandi, R.L.; et al. Targeting IL-17A in Multiple Myeloma: A Potential Novel Therapeutic Approach in Myeloma. Leukemia 2016, 30, 379–389. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  123. Suen, H.; Brown, R.; Yang, S.; Weatherburn, C.; Ho, P.J.; Woodland, N.; Nassif, N.; Barbaro, P.; Bryant, C.; Hart, D.; et al. Multiple Myeloma Causes Clonal T-Cell Immunosenescence: Identification of Potential Novel Targets for Promoting Tumour Immunity and Implications for Checkpoint Blockade. Leukemia 2016, 30, 1716–1724. [Google Scholar] [CrossRef] [PubMed]
  124. Das, R.K.; Vernau, L.; Grupp, S.A.; Barrett, D.M. Naïve T-Cell Deficits at Diagnosis and after Chemotherapy Impair Cell Therapy Potential in Pediatric Cancers. Cancer Discov. 2019, 9, 492–499. [Google Scholar] [CrossRef] [Green Version]
  125. Arasanz, H.; Zuazo, M.; Bocanegra, A.; Gato, M.; Martínez-Aguillo, M.; Morilla, I.; Fernández, G.; Hernández, B.; López, P.; Alberdi, N.; et al. Early Detection of Hyperprogressive Disease in Non-Small Cell Lung Cancer by Monitoring of Systemic T Cell Dynamics. Cancers 2020, 12, 344. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  126. Battram, A.M.; Bachiller, M.; Lopez, V.; Fernández de Larrea, C.; Urbano-Ispizua, A.; Martín-Antonio, B. IL-15 Enhances the Persistence and Function of BCMA-Targeting CAR-T Cells Compared to IL-2 or IL-15/IL-7 by Limiting CAR-T Cell Dysfunction and Differentiation. Cancers 2021, 13, 3534. [Google Scholar] [CrossRef] [PubMed]
  127. Lanna, A.; Gomes, D.C.O.; Muller-Durovic, B.; McDonnell, T.; Escors, D.; Gilroy, D.W.; Lee, J.H.; Karin, M.; Akbar, A.N. A Sestrin-Dependent Erk-Jnk-P38 MAPK Activation Complex Inhibits Immunity during Aging. Nat. Immunol. 2017, 18, 354–363. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  128. Jinushi, M.; Vanneman, M.; Munshi, N.C.; Tai, Y.-T.; Prabhala, R.H.; Ritz, J.; Neuberg, D.; Anderson, K.C.; Carrasco, D.R.; Dranoff, G. MHC Class I Chain-Related Protein A Antibodies and Shedding Are Associated with the Progression of Multiple Myeloma. Proc. Natl. Acad. Sci. USA 2008, 105, 1285–1290. [Google Scholar] [CrossRef] [Green Version]
  129. Benson, D.M., Jr.; Bakan, C.E.; Mishra, A.; Hofmeister, C.C.; Efebera, Y.; Becknell, B.; Baiocchi, R.A.; Zhang, J.; Yu, J.; Smith, M.K.; et al. The PD-1/PD-L1 Axis Modulates the Natural Killer Cell versus Multiple Myeloma Effect: A Therapeutic Target for CT-011, a Novel Monoclonal Anti–PD-1 Antibody. Blood 2010, 116, 2286–2294. [Google Scholar] [CrossRef]
  130. Pazina, T.; MacFarlane, A.W.; Bernabei, L.; Dulaimi, E.; Kotcher, R.; Yam, C.; Bezman, N.A.; Robbins, M.D.; Ross, E.A.; Campbell, K.S.; et al. Alterations of NK Cell Phenotype in the Disease Course of Multiple Myeloma. Cancers 2021, 13, 226. [Google Scholar] [CrossRef]
  131. Cifaldi, L.; Prencipe, G.; Caiello, I.; Bracaglia, C.; Locatelli, F.; De Benedetti, F.; Strippoli, R. Inhibition of Natural Killer Cell Cytotoxicity by Interleukin-6: Implications for the Pathogenesis of Macrophage Activation Syndrome. Arthritis Rheumatol. 2015, 67, 3037–3046. [Google Scholar] [CrossRef]
  132. Tamura, H.; Ishibashi, M.; Yamashita, T.; Tanosaki, S.; Okuyama, N.; Kondo, A.; Hyodo, H.; Shinya, E.; Takahashi, H.; Dong, H.; et al. Marrow Stromal Cells Induce B7-H1 Expression on Myeloma Cells, Generating Aggressive Characteristics in Multiple Myeloma. Leukemia 2013, 27, 464–472. [Google Scholar] [CrossRef] [Green Version]
  133. Tamura, H.; Ishibashi, M.; Sunakawa-Kii, M.; Inokuchi, K. PD-L1-PD-1 Pathway in the Pathophysiology of Multiple Myeloma. Cancers 2020, 12, 924. [Google Scholar] [CrossRef]
  134. Elkabets, M.; Ribeiro, V.S.G.; Dinarello, C.A.; Ostrand-Rosenberg, S.; Di Santo, J.P.; Apte, R.N.; Vosshenrich, C.A.J. IL-1β Regulates a Novel Myeloid-Derived Suppressor Cell Subset That Impairs NK Cell Development and Function. Eur. J. Immunol. 2010, 40, 3347–3357. [Google Scholar] [CrossRef]
  135. Ponzetta, A.; Benigni, G.; Antonangeli, F.; Sciumè, G.; Sanseviero, E.; Zingoni, A.; Ricciardi, M.R.; Petrucci, M.T.; Santoni, A.; Bernardini, G. Multiple Myeloma Impairs Bone Marrow Localization of Effector Natural Killer Cells by Altering the Chemokine Microenvironment. Cancer Res. 2015, 75, 4766–4777. [Google Scholar] [CrossRef] [Green Version]
  136. Clara, J.A.; Childs, R.W. Harnessing Natural Killer Cells for the Treatment of Multiple Myeloma. Semin. Oncol. 2022, 49, 69–85. [Google Scholar] [CrossRef]
  137. Bachiller, M.; Battram, A.M.; Perez-Amill, L.; Martín-Antonio, B. Natural Killer Cells in Immunotherapy: Are We Nearly There? Cancers 2020, 12, 3139. [Google Scholar] [CrossRef]
  138. Flores-Borja, F.; Bosma, A.; Ng, D.; Reddy, V.; Ehrenstein, M.R.; Isenberg, D.A.; Mauri, C. CD19+CD24hiCD38hi B Cells Maintain Regulatory T Cells While Limiting TH1 and TH17 Differentiation. Sci. Transl. Med. 2013, 5, 173ra23. [Google Scholar] [CrossRef]
  139. Zhang, L.; Tai, Y.-T.; Ho, M.; Xing, L.; Chauhan, D.; Gang, A.; Qiu, L.; Anderson, K.C. Regulatory B Cell-Myeloma Cell Interaction Confers Immunosuppression and Promotes Their Survival in the Bone Marrow Milieu. Blood Cancer J. 2017, 7, e547. [Google Scholar] [CrossRef] [Green Version]
  140. Beider, K.; Bitner, H.; Leiba, M.; Gutwein, O.; Koren-Michowitz, M.; Ostrovsky, O.; Abraham, M.; Wald, H.; Galun, E.; Peled, A.; et al. Multiple Myeloma Cells Recruit Tumor-Supportive Macrophages through the CXCR4/CXCL12 Axis and Promote Their Polarization toward the M2 Phenotype. Oncotarget 2014, 5, 11283–11296. [Google Scholar] [CrossRef] [Green Version]
  141. Andersen, M.N.; Andersen, N.F.; Rødgaard-Hansen, S.; Hokland, M.; Abildgaard, N.; Møller, H.J. The Novel Biomarker of Alternative Macrophage Activation, Soluble Mannose Receptor (SMR/SCD206): Implications in Multiple Myeloma. Leuk. Res. 2015, 39, 971–975. [Google Scholar] [CrossRef]
  142. Xu, R.; Li, Y.; Yan, H.; Zhang, E.; Huang, X.; Chen, Q.; Chen, J.; Qu, J.; Liu, Y.; He, J.; et al. CCL2 Promotes Macrophages-Associated Chemoresistance via MCPIP1 Dual Catalytic Activities in Multiple Myeloma. Cell Death Dis. 2019, 10, 781. [Google Scholar] [CrossRef]
  143. Russ, A.; Hua, A.B.; Montfort, W.R.; Rahman, B.; Riaz, I.B.; Khalid, M.U.; Carew, J.S.; Nawrocki, S.T.; Persky, D.; Anwer, F. Blocking “Don’t Eat Me” Signal of CD47-SIRPα in Hematological Malignancies, an in-Depth Review. Blood Rev. 2018, 32, 480–489. [Google Scholar] [CrossRef]
  144. Opperman, K.S.; Vandyke, K.; Clark, K.C.; Coulter, E.A.; Hewett, D.R.; Mrozik, K.M.; Schwarz, N.; Evdokiou, A.; Croucher, P.I.; Psaltis, P.J.; et al. Clodronate-Liposome Mediated Macrophage Depletion Abrogates Multiple Myeloma Tumor Establishment In Vivo. Neoplasia 2019, 21, 777–787. [Google Scholar] [CrossRef]
  145. Ries, C.H.; Cannarile, M.A.; Hoves, S.; Benz, J.; Wartha, K.; Runza, V.; Rey-Giraud, F.; Pradel, L.P.; Feuerhake, F.; Klaman, I.; et al. Targeting Tumor-Associated Macrophages with Anti-CSF-1R Antibody Reveals a Strategy for Cancer Therapy. Cancer Cell 2014, 25, 846–859. [Google Scholar] [CrossRef] [Green Version]
  146. Görgün, G.T.; Whitehill, G.; Anderson, J.L.; Hideshima, T.; Maguire, C.; Laubach, J.; Raje, N.; Munshi, N.C.; Richardson, P.G.; Anderson, K.C. Tumor-Promoting Immune-Suppressive Myeloid-Derived Suppressor Cells in the Multiple Myeloma Microenvironment in Humans. Blood 2013, 121, 2975–2987. [Google Scholar] [CrossRef] [Green Version]
  147. Jakubowiak, A.J.; Kumar, S.; Medhekar, R.; Pei, H.; Lefebvre, P.; Kaila, S.; He, J.; Lafeuille, M.-H.; Cortoos, A.; Londhe, A.; et al. Daratumumab Improves Depth of Response and Progression-Free Survival in Transplant-Ineligible, High-Risk, Newly Diagnosed Multiple Myeloma. Oncologist 2022, 27, e589–e596. [Google Scholar] [CrossRef] [PubMed]
  148. Htut, M.; Gasparetto, C.; Zonder, J.; Martin, T.G., III; Scott, E.C.; Chen, J.; Shemesh, S.; Brooks, C.L.; Chauhan, D.; Anderson, K.C.; et al. Results from Ongoing Phase 1/2 Trial of SL-401 in Combination with Pomalidomide and Dexamethasone in Relapsed or Refractory Multiple Myeloma. Blood 2016, 128, 5696. [Google Scholar] [CrossRef]
  149. Rossi, M.; Botta, C.; Correale, P.; Tassone, P.; Tagliaferri, P. Immunologic Microenvironment and Personalized Treatment in Multiple Myeloma. Expert Opin. Biol. Ther. 2013, 13 (Suppl. S1), S83–S93. [Google Scholar] [CrossRef]
  150. Yamamoto, L.; Amodio, N.; Gulla, A.; Anderson, K.C. Harnessing the Immune System Against Multiple Myeloma: Challenges and Opportunities. Front. Oncol. 2021, 10, 606368. [Google Scholar] [CrossRef] [PubMed]
  151. Moser-Katz, T.; Joseph, N.S.; Dhodapkar, M.V.; Lee, K.P.; Boise, L.H. Game of Bones: How Myeloma Manipulates Its Microenvironment. Front. Oncol. 2021, 10, 625199. [Google Scholar] [CrossRef] [PubMed]
  152. Nakamura, K.; Smyth, M.J.; Martinet, L. Cancer Immunoediting and Immune Dysregulation in Multiple Myeloma. Blood 2020, 136, 2731–2740. [Google Scholar] [CrossRef]
  153. Whiteside, T.L. The Tumor Microenvironment and Its Role in Promoting Tumor Growth. Oncogene 2008, 27, 5904–5912. [Google Scholar] [CrossRef] [Green Version]
  154. Kay, N.E.; Leong, T.L.; Bone, N.; Vesole, D.H.; Greipp, P.R.; Van Ness, B.; Oken, M.M.; Kyle, R.A. Blood Levels of Immune Cells Predict Survival in Myeloma Patients: Results of an Eastern Cooperative Oncology Group Phase 3 Trial for Newly Diagnosed Multiple Myeloma Patients. Blood 2001, 98, 23–28. [Google Scholar] [CrossRef]
  155. Raitakari, M.; Brown, R.D.; Gibson, J.; Joshua, D.E. T Cells in Myeloma. Hematol. Oncol. 2003, 21, 33–42. [Google Scholar] [CrossRef]
  156. Wei, F.; Cheng, X.-X.; Xue, J.Z.; Xue, S.-A. Emerging Strategies in TCR-Engineered T Cells. Front. Immunol. 2022, 13, 850358. [Google Scholar] [CrossRef]
  157. Kasakovski, D.; Xu, L.; Li, Y. T Cell Senescence and CAR-T Cell Exhaustion in Hematological Malignancies. J. Hematol. Oncol. 2018, 11, 91. [Google Scholar] [CrossRef]
  158. Ab Rahman, A.S.; Strother, R.M.; Paddison, J. New Zealand National Retrospective Cohort Study of Survival Outcomes of Patients with Metastatic Melanoma Receiving Immune-Checkpoint Inhibitors. Asia Pac. J. Clin. Oncol. 2022, 1–8. [Google Scholar] [CrossRef]
  159. Das, S.; Johnson, D.B. Immune-Related Adverse Events and Anti-Tumor Efficacy of Immune Checkpoint Inhibitors. J. Immunother. Cancer 2019, 7, 306. [Google Scholar] [CrossRef]
  160. Yamazaki, N.; Uhara, H.; Fukushima, S.; Uchi, H.; Shibagaki, N.; Kiyohara, Y.; Tsutsumida, A.; Namikawa, K.; Okuyama, R.; Otsuka, Y.; et al. Phase II Study of the Immune-Checkpoint Inhibitor Ipilimumab plus Dacarbazine in Japanese Patients with Previously Untreated, Unresectable or Metastatic Melanoma. Cancer Chemother. Pharm. 2015, 76, 969–975. [Google Scholar] [CrossRef] [Green Version]
  161. Miller, B.C.; Sen, D.R.; Al Abosy, R.; Bi, K.; Virkud, Y.V.; LaFleur, M.W.; Yates, K.B.; Lako, A.; Felt, K.; Naik, G.S.; et al. Subsets of Exhausted CD8+ T Cells Differentially Mediate Tumor Control and Respond to Checkpoint Blockade. Nat. Immunol. 2019, 20, 326–336. [Google Scholar] [CrossRef]
  162. Zelle-Rieser, C.; Thangavadivel, S.; Biedermann, R.; Brunner, A.; Stoitzner, P.; Willenbacher, E.; Greil, R.; Jöhrer, K. T Cells in Multiple Myeloma Display Features of Exhaustion and Senescence at the Tumor Site. J. Hematol. Oncol. 2016, 9, 116. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  163. Visram, A.; Kourelis, T.V. Aging-Associated Immune System Changes in Multiple Myeloma: The Dark Side of the Moon. Cancer Treat. Res. Commun. 2021, 29, 100494. [Google Scholar] [CrossRef]
  164. Frassanito, M.A.; Cusmai, A.; Iodice, G.; Dammacco, F. Autocrine Interleukin-6 Production and Highly Malignant Multiple Myeloma: Relation with Resistance to Drug-Induced Apoptosis. Blood 2001, 97, 483–489. [Google Scholar] [CrossRef]
  165. Fontenot, J.D.; Gavin, M.A.; Rudensky, A.Y. Foxp3 Programs the Development and Function of CD4+CD25+ Regulatory T Cells. Nat. Immunol. 2003, 4, 330–336. [Google Scholar] [CrossRef] [PubMed]
  166. Workman, C.J.; Szymczak-Workman, A.L.; Collison, L.W.; Pillai, M.R.; Vignali, D.A.A. The Development and Function of Regulatory T Cells. Cell Mol. Life Sci. 2009, 66, 2603–2622. [Google Scholar] [CrossRef] [Green Version]
  167. Curiel, T.J. Regulatory T Cells and Treatment of Cancer. Curr. Opin. Immunol. 2008, 20, 241–246. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  168. Hadjiaggelidou, C.; Katodritou, E. Regulatory T-Cells and Multiple Myeloma: Implications in Tumor Immune Biology and Treatment. J. Clin. Med. 2021, 10, 4588. [Google Scholar] [CrossRef] [PubMed]
  169. Raja, K.R.M.; Rihova, L.; Zahradova, L.; Klincova, M.; Penka, M.; Hajek, R. Increased T Regulatory Cells Are Associated with Adverse Clinical Features and Predict Progression in Multiple Myeloma. PLoS ONE 2012, 7, e47077. [Google Scholar] [CrossRef]
  170. Prabhala, R.H.; Neri, P.; Bae, J.E.; Tassone, P.; Shammas, M.A.; Allam, C.K.; Daley, J.F.; Chauhan, D.; Blanchard, E.; Thatte, H.S.; et al. Dysfunctional T Regulatory Cells in Multiple Myeloma. Blood 2006, 107, 301–304. [Google Scholar] [CrossRef] [Green Version]
  171. Noonan, K.; Marchionni, L.; Anderson, J.; Pardoll, D.; Roodman, G.D.; Borrello, I. A Novel Role of IL-17–Producing Lymphocytes in Mediating Lytic Bone Disease in Multiple Myeloma. Blood 2010, 116, 3554–3563. [Google Scholar] [CrossRef] [Green Version]
  172. Foglietta, M.; Castella, B.; Mariani, S.; Coscia, M.; Godio, L.; Ferracini, R.; Ruggeri, M.; Muccio, V.; Omedé, P.; Palumbo, A.; et al. The Bone Marrow of Myeloma Patients Is Steadily Inhabited by a Normal-Sized Pool of Functional Regulatory T Cells Irrespectiveof the Disease Status. Haematologica 2014, 99, 1605–1610. [Google Scholar] [CrossRef] [Green Version]
  173. Sun, L.; Fu, J.; Zhou, Y. Metabolism Controls the Balance of Th17/T-Regulatory Cells. Front. Immunol. 2017, 8, 1632. [Google Scholar] [CrossRef] [Green Version]
  174. Rossi, M.; Altomare, E.; Botta, C.; Gallo Cantafio, M.E.; Sarvide, S.; Caracciolo, D.; Riillo, C.; Gaspari, M.; Taverna, D.; Conforti, F.; et al. MiR-21 Antagonism Abrogates Th17 Tumor Promoting Functions in Multiple Myeloma. Leukemia 2021, 35, 823–834. [Google Scholar] [CrossRef]
  175. Ma, T.; Zhang, Y.; Zhou, X.; Xie, P.; Li, J. A Unique Role of T Helper 17 Cells in Different Treatment Stages of Multiple Myeloma. Clin. Lymphoma Myeloma Leuk. 2020, 20, 190–197. [Google Scholar] [CrossRef] [Green Version]
  176. Dhodapkar, K.M.; Barbuto, S.; Matthews, P.; Kukreja, A.; Mazumder, A.; Vesole, D.; Jagannath, S.; Dhodapkar, M.V. Dendritic Cells Mediate the Induction of Polyfunctional Human IL17-Producing Cells (Th17-1 Cells) Enriched in the Bone Marrow of Patients with Myeloma. Blood 2008, 112, 2878–2885. [Google Scholar] [CrossRef]
  177. Kale, A.; Sharma, A.; Stolzing, A.; Desprez, P.-Y.; Campisi, J. Role of Immune Cells in the Removal of Deleterious Senescent Cells. Immun. Ageing 2020, 17, 16. [Google Scholar] [CrossRef]
  178. Iannello, A.; Thompson, T.W.; Ardolino, M.; Lowe, S.W.; Raulet, D.H. P53-Dependent Chemokine Production by Senescent Tumor Cells Supports NKG2D-Dependent Tumor Elimination by Natural Killer Cells. J. Exp. Med. 2013, 210, 2057–2069. [Google Scholar] [CrossRef]
  179. Liu, Q.; Sun, Z.; Chen, L. Memory T Cells: Strategies for Optimizing Tumor Immunotherapy. Protein Cell 2020, 11, 549–564. [Google Scholar] [CrossRef] [Green Version]
  180. Thomas, R.; Wang, W.; Su, D.-M. Contributions of Age-Related Thymic Involution to Immunosenescence and Inflammaging. Immun. Ageing 2020, 17, 2. [Google Scholar] [CrossRef] [Green Version]
  181. Coder, B.D.; Wang, H.; Ruan, L.; Su, D.-M. Thymic Involution Perturbs Negative Selection Leading to Autoreactive T Cells That Induce Chronic Inflammation. J. Immunol. 2015, 194, 5825–5837. [Google Scholar] [CrossRef] [Green Version]
  182. Rodrigues, L.P.; Teixeira, V.R.; Alencar-Silva, T.; Simonassi-Paiva, B.; Pereira, R.W.; Pogue, R.; Carvalho, J.L. Hallmarks of Aging and Immunosenescence: Connecting the Dots. Cytokine Growth Factor Rev. 2021, 59, 9–21. [Google Scholar] [CrossRef] [PubMed]
  183. Rodriguez, I.J.; Lalinde Ruiz, N.; Llano León, M.; Martínez Enríquez, L.; del Montilla Velásquez, M.P.; Ortiz Aguirre, J.P.; Rodríguez Bohórquez, O.M.; Velandia Vargas, E.A.; Hernández, E.D.; Parra López, C.A. Immunosenescence Study of T Cells: A Systematic Review. Front. Immunol. 2021, 11, 3460. [Google Scholar] [CrossRef] [PubMed]
  184. Fahy, G.M.; Brooke, R.T.; Watson, J.P.; Good, Z.; Vasanawala, S.S.; Maecker, H.; Leipold, M.D.; Lin, D.T.S.; Kobor, M.S.; Horvath, S. Reversal of Epigenetic Aging and Immunosenescent Trends in Humans. Aging Cell 2019, 18, e13028. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  185. Gao, J.; Zhao, L.; Wan, Y.Y.; Zhu, B. Mechanism of Action of IL-7 and Its Potential Applications and Limitations in Cancer Immunotherapy. Int. J. Mol. Sci. 2015, 16, 10267–10280. [Google Scholar] [CrossRef] [Green Version]
  186. Di Mitri, D.; Azevedo, R.I.; Henson, S.M.; Libri, V.; Riddell, N.E.; Macaulay, R.; Kipling, D.; Soares, M.V.D.; Battistini, L.; Akbar, A.N. Reversible Senescence in Human CD4+CD45RA+CD27- Memory T Cells. J. Immunol. 2011, 187, 2093–2100. [Google Scholar] [CrossRef] [Green Version]
  187. Aiello, A.; Farzaneh, F.; Candore, G.; Caruso, C.; Davinelli, S.; Gambino, C.M.; Ligotti, M.E.; Zareian, N.; Accardi, G. Immunosenescence and Its Hallmarks: How to Oppose Aging Strategically? A Review of Potential Options for Therapeutic Intervention. Front. Immunol. 2019, 10, 2247. [Google Scholar] [CrossRef] [Green Version]
  188. Mannick, J.B.; Morris, M.; Hockey, H.-U.P.; Roma, G.; Beibel, M.; Kulmatycki, K.; Watkins, M.; Shavlakadze, T.; Zhou, W.; Quinn, D.; et al. TORC1 Inhibition Enhances Immune Function and Reduces Infections in the Elderly. Sci. Transl. Med. 2018, 10, eaaq1564. [Google Scholar] [CrossRef] [Green Version]
  189. Weichhart, T.; Haidinger, M.; Katholnig, K.; Kopecky, C.; Poglitsch, M.; Lassnig, C.; Rosner, M.; Zlabinger, G.J.; Hengstschläger, M.; Müller, M.; et al. Inhibition of MTOR Blocks the Anti-Inflammatory Effects of Glucocorticoids in Myeloid Immune Cells. Blood 2011, 117, 4273–4283. [Google Scholar] [CrossRef] [Green Version]
  190. El-Sherbiny, Y.M.; Meade, J.L.; Holmes, T.D.; McGonagle, D.; Mackie, S.L.; Morgan, A.W.; Cook, G.; Feyler, S.; Richards, S.J.; Davies, F.E.; et al. The Requirement for DNAM-1, NKG2D, and NKp46 in the Natural Killer Cell-Mediated Killing of Myeloma Cells. Cancer Res. 2007, 67, 8444–8449. [Google Scholar] [CrossRef] [Green Version]
  191. Blom, B.; van Hoeven, V.; Hazenberg, M.D. ILCs in Hematologic Malignancies: Tumor Cell Killers and Tissue Healers. Semin. Immunol. 2019, 41, 101279. [Google Scholar] [CrossRef]
  192. Martín-Antonio, B.; Suñe, G.; Perez-Amill, L.; Castella, M.; Urbano-Ispizua, A. Natural Killer Cells: Angels and Devils for Immunotherapy. Int. J. Mol. Sci. 2017, 18, 1868. [Google Scholar] [CrossRef] [Green Version]
  193. Martín-Antonio, B.; Suñe, G.; Najjar, A.; Perez-Amill, L.; Antoñana-Vildosola, A.; Castella, M.; León, S.; Velasco-de Andrés, M.; Lozano, F.; Lozano, E.; et al. Extracellular NK Histones Promote Immune Cell Anti-Tumor Activity by Inducing Cell Clusters through Binding to CD138 Receptor. J. Immunother. Cancer 2019, 7, 259. [Google Scholar] [CrossRef]
  194. Carbone, E.; Neri, P.; Mesuraca, M.; Fulciniti, M.T.; Otsuki, T.; Pende, D.; Groh, V.; Spies, T.; Pollio, G.; Cosman, D.; et al. HLA Class I, NKG2D, and Natural Cytotoxicity Receptors Regulate Multiple Myeloma Cell Recognition by Natural Killer Cells. Blood 2005, 105, 251–258. [Google Scholar] [CrossRef] [Green Version]
  195. Nersesian, S.; Schwartz, S.L.; Grantham, S.R.; MacLean, L.K.; Lee, S.N.; Pugh-Toole, M.; Boudreau, J.E. NK Cell Infiltration Is Associated with Improved Overall Survival in Solid Cancers: A Systematic Review and Meta-Analysis. Transl. Oncol. 2021, 14, 100930. [Google Scholar] [CrossRef]
  196. Konjević, G.; Vuletić, A.; Mirjačić Martinović, K.; Colović, N.; Čolović, M.; Jurišić, V. Decreased CD161 Activating and Increased CD158a Inhibitory Receptor Expression on NK Cells Underlies Impaired NK Cell Cytotoxicity in Patients with Multiple Myeloma. J. Clin. Pathol. 2016, 69, 1009–1016. [Google Scholar] [CrossRef]
  197. Hanna, J.; Goldman-Wohl, D.; Hamani, Y.; Avraham, I.; Greenfield, C.; Natanson-Yaron, S.; Prus, D.; Cohen-Daniel, L.; Arnon, T.I.; Manaster, I.; et al. Decidual NK Cells Regulate Key Developmental Processes at the Human Fetal-Maternal Interface. Nat. Med. 2006, 12, 1065–1074. [Google Scholar] [CrossRef]
  198. Jabrane-Ferrat, N. Features of Human Decidual NK Cells in Healthy Pregnancy and During Viral Infection. Front. Immunol. 2019, 10, 1397. [Google Scholar] [CrossRef]
  199. Fu, B.; Zhou, Y.; Ni, X.; Tong, X.; Xu, X.; Dong, Z.; Sun, R.; Tian, Z.; Wei, H. Natural Killer Cells Promote Fetal Development through the Secretion of Growth-Promoting Factors. Immunity 2017, 47, 1100–1113.e6. [Google Scholar] [CrossRef] [Green Version]
  200. Sojka, D.K.; Yang, L.; Yokoyama, W.M. Uterine Natural Killer Cells. Front. Immunol. 2019, 10, 960. [Google Scholar] [CrossRef]
  201. Huhn, O.; Zhao, X.; Esposito, L.; Moffett, A.; Colucci, F.; Sharkey, A.M. How Do Uterine Natural Killer and Innate Lymphoid Cells Contribute to Successful Pregnancy? Front. Immunol. 2021, 12, 607669. [Google Scholar] [CrossRef]
  202. Shah, N.; Martin-Antonio, B.; Yang, H.; Ku, S.; Lee, D.A.; Cooper, L.J.N.; Decker, W.K.; Li, S.; Robinson, S.N.; Sekine, T.; et al. Antigen Presenting Cell-Mediated Expansion of Human Umbilical Cord Blood Yields Log-Scale Expansion of Natural Killer Cells with Anti-Myeloma Activity. PLoS ONE 2013, 8, e76781. [Google Scholar] [CrossRef]
  203. Martin-Antonio, B.; Najjar, A.; Robinson, S.N.; Chew, C.; Li, S.; Yvon, E.; Thomas, M.W.; Mc Niece, I.; Orlowski, R.; Muñoz-Pinedo, C.; et al. Transmissible Cytotoxicity of Multiple Myeloma Cells by Cord Blood-Derived NK Cells Is Mediated by Vesicle Trafficking. Cell Death Differ. 2015, 22, 96–107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  204. Cai, X.; Zhang, L.; Wei, W. Regulatory B Cells in Inflammatory Diseases and Tumor. Int. Immunopharmacol. 2019, 67, 281–286. [Google Scholar] [CrossRef]
  205. Zhou, M.; Wen, Z.; Cheng, F.; Ma, J.; Li, W.; Ren, H.; Sheng, Y.; Dong, H.; Lu, L.; Hu, H.-M.; et al. Tumor-Released Autophagosomes Induce IL-10-Producing B Cells with Suppressive Activity on T Lymphocytes via TLR2-MyD88-NF-ΚB Signal Pathway. Oncoimmunology 2016, 5, e1180485. [Google Scholar] [CrossRef] [PubMed]
  206. Zou, Z.; Guo, T.; Cui, J.; Zhang, L.; Pan, L. Onset of Regulatory B Cells Occurs at Initial Stage of B Cell Dysfunction in Multiple Myeloma. Blood 2019, 134, 1780. [Google Scholar] [CrossRef]
  207. Zheng, Y.; Cai, Z.; Wang, S.; Zhang, X.; Qian, J.; Hong, S.; Li, H.; Wang, M.; Yang, J.; Yi, Q. Macrophages Are an Abundant Component of Myeloma Microenvironment and Protect Myeloma Cells from Chemotherapy Drug-Induced Apoptosis. Blood 2009, 114, 3625–3628. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  208. Zheng, Y.; Yang, J.; Qian, J.; Qiu, P.; Hanabuchi, S.; Lu, Y.; Wang, Z.; Liu, Z.; Li, H.; He, J.; et al. PSGL-1/Selectin and ICAM-1/CD18 Interactions Are Involved in Macrophage-Induced Drug Resistance in Myeloma. Leukemia 2013, 27, 702–710. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  209. Wang, H.; Hu, W.; Xia, Z.; Liang, Y.; Lu, Y.; Lin, S.; Tang, H. High Numbers of CD163+ Tumor-Associated Macrophages Correlate with Poor Prognosis in Multiple Myeloma Patients Receiving Bortezomib-Based Regimens. J. Cancer 2019, 10, 3239–3245. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  210. Murray, P.J. Macrophage Polarization. Annu. Rev. Physiol. 2017, 79, 541–566. [Google Scholar] [CrossRef]
  211. Khalife, J.; Ghose, J.; Martella, M.; Viola, D.; Rocci, A.; Troadec, E.; Terrazas, C.; Satoskar, A.R.; Gunes, E.G.; Dona, A.; et al. MiR-16 Regulates Crosstalk in NF-ΚB Tolerogenic Inflammatory Signaling between Myeloma Cells and Bone Marrow Macrophages. JCI Insight 2019, 4, 129348. [Google Scholar] [CrossRef]
  212. Wang, Q.; Lu, Y.; Li, R.; Jiang, Y.; Zheng, Y.; Qian, J.; Bi, E.; Zheng, C.; Hou, J.; Wang, S.; et al. Therapeutic Effects of CSF1R-Blocking Antibodies in Multiple Myeloma. Leukemia 2018, 32, 176–183. [Google Scholar] [CrossRef] [PubMed]
  213. Sun, J.; Park, C.; Guenthner, N.; Gurley, S.; Zhang, L.; Lubben, B.; Adebayo, O.; Bash, H.; Chen, Y.; Maksimos, M.; et al. Tumor-Associated Macrophages in Multiple Myeloma: Advances in Biology and Therapy. J Immunother. Cancer 2022, 10, e003975. [Google Scholar] [CrossRef] [PubMed]
  214. Favaloro, J.; Liyadipitiya, T.; Brown, R.; Yang, S.; Suen, H.; Woodland, N.; Nassif, N.; Hart, D.; Fromm, P.; Weatherburn, C.; et al. Myeloid Derived Suppressor Cells Are Numerically, Functionally and Phenotypically Different in Patients with Multiple Myeloma. Leuk. Lymphoma 2014, 55, 2893–2900. [Google Scholar] [CrossRef] [PubMed]
  215. De Veirman, K.; Van Ginderachter, J.A.; Lub, S.; De Beule, N.; Thielemans, K.; Bautmans, I.; Oyajobi, B.O.; De Bruyne, E.; Menu, E.; Lemaire, M.; et al. Multiple Myeloma Induces Mcl-1 Expression and Survival of Myeloid-Derived Suppressor Cells. Oncotarget 2015, 6, 10532–10547. [Google Scholar] [CrossRef] [Green Version]
  216. Lee, S.-E.; Lim, J.-Y.; Ryu, D.-B.; Kim, T.W.; Yoon, J.-H.; Cho, B.-S.; Eom, K.-S.; Kim, Y.-J.; Kim, H.-J.; Lee, S.; et al. Circulating Immune Cell Phenotype Can Predict the Outcome of Lenalidomide plus Low-Dose Dexamethasone Treatment in Patients with Refractory/Relapsed Multiple Myeloma. Cancer Immunol. Immunother. 2016, 65, 983–994. [Google Scholar] [CrossRef]
  217. Wang, J.; Veirman, K.D.; Beule, N.D.; Maes, K.; Bruyne, E.D.; Valckenborgh, E.V.; Vanderkerken, K.; Menu, E. The Bone Marrow Microenvironment Enhances Multiple Myeloma Progression by Exosome-Mediated Activation of Myeloid-Derived Suppressor Cells. Oncotarget 2015, 6, 43992–44004. [Google Scholar] [CrossRef] [Green Version]
  218. Uckun, F.M. Dual Targeting of Multiple Myeloma Stem Cells and Myeloid-Derived Suppressor Cells for Treatment of Chemotherapy-Resistant Multiple Myeloma. Front. Oncol. 2021, 11, 760382. [Google Scholar] [CrossRef]
  219. Li, K.; Shi, H.; Zhang, B.; Ou, X.; Ma, Q.; Chen, Y.; Shu, P.; Li, D.; Wang, Y. Myeloid-Derived Suppressor Cells as Immunosuppressive Regulators and Therapeutic Targets in Cancer. Sig. Transduct. Target. Ther. 2021, 6, 362. [Google Scholar] [CrossRef]
Figure 1. Summary of the interactions between non-hematological cells and multiple myeloma (MM) cells in the bone marrow (BM): Different cell populations interacting with MM, receptors involved and secreted molecules by the different cell subsets that impact MM cell proliferation are indicated. The extracellular matrix (ECM) causes an attraction of MM cells to the BM. Bone marrow mesenchymal stromal cells (BM-MSCs) and MM cells interact, making the stroma a favorable environment for MM cells. MM cells and BM-MSCs alter the balance between osteoblast formation and osteoclast degradation. Endothelial cells enhance the angiogenesis in the BM to favor extramedullary disease.
Figure 1. Summary of the interactions between non-hematological cells and multiple myeloma (MM) cells in the bone marrow (BM): Different cell populations interacting with MM, receptors involved and secreted molecules by the different cell subsets that impact MM cell proliferation are indicated. The extracellular matrix (ECM) causes an attraction of MM cells to the BM. Bone marrow mesenchymal stromal cells (BM-MSCs) and MM cells interact, making the stroma a favorable environment for MM cells. MM cells and BM-MSCs alter the balance between osteoblast formation and osteoclast degradation. Endothelial cells enhance the angiogenesis in the BM to favor extramedullary disease.
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Figure 2. Summary of the impact that secreted molecules or expression of receptors by MM cells cause on the polarization and activity of immune cells. MM cells directly generate functional T regulatory (T-reg) cells contact-dependent by ICOS/ICOS-L. IL6 and IL21 secretion in the BM causes a decrease in the T helper (Th)1 cell populations leading to an imbalanced Th1/Th2 ratio. IL6 and IL21 secretion by MM cells enhance the production of Th17 cells. Over-expression of ligands of immune-checkpoint receptors in T cells causes exhaustion of T cells and natural killer (NK) cells. Secretion of IL10, CCL5, MIP-1, and IL6 from MM cells generates MDSCs with T cell suppressive ability. CXCL12 production and secretion of extracellular vesicles (EVs) by MM cells increases monocyte and induces M2 macrophage polarization.
Figure 2. Summary of the impact that secreted molecules or expression of receptors by MM cells cause on the polarization and activity of immune cells. MM cells directly generate functional T regulatory (T-reg) cells contact-dependent by ICOS/ICOS-L. IL6 and IL21 secretion in the BM causes a decrease in the T helper (Th)1 cell populations leading to an imbalanced Th1/Th2 ratio. IL6 and IL21 secretion by MM cells enhance the production of Th17 cells. Over-expression of ligands of immune-checkpoint receptors in T cells causes exhaustion of T cells and natural killer (NK) cells. Secretion of IL10, CCL5, MIP-1, and IL6 from MM cells generates MDSCs with T cell suppressive ability. CXCL12 production and secretion of extracellular vesicles (EVs) by MM cells increases monocyte and induces M2 macrophage polarization.
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Table 1. MM the cell–cell interactions and molecules involved in the interactions that may affect disease progression and the anti-MM therapies that could target these interactions.
Table 1. MM the cell–cell interactions and molecules involved in the interactions that may affect disease progression and the anti-MM therapies that could target these interactions.
Cellular Compartment or ProcessMolecules and/or Cell Population InvolvedImpact on MM DiseaseTherapeutic Strategy Proposed
ECM1. CXCR4/CXCL12.
2. CD138 and VLA-4 (MM)/Fibronectin (ECM).
1. MM homing into the BM [30].
2. NFkB activation, tumor survival, drug resistance [32].
1–2: AMD3100 (CXCR4 inhibitor), and Bortezomib (VLA-4 downregulation) [34].
BM-MSCs1. VLA-4 (MM)/VCAM-1 (BM-MSCs).
2. LFA-1 (MM)/ICAM-1 (BM-MSCs).
3. IL6 secretion by BM-MSCs induced by MM cells.
4. Notch pathways and DKK1.
5. LINC00461 in BM-MSCs exosomes
6. Ligation of BAFF.
7. APRIL secretion (BM-MSCs)/BCMA and TACI (MM) [51]
8. TNFα.
1. NFkB activation, MM survival [39].
2. Disease progression [40].
3. Enhanced secretion of VEGF and bFGF by MM that re-stimulates IL6 production [43].
4. IL6, VEGF, and IGF-1 secretion in BM-MSCs [46,47].
5. MM cell proliferation and drug resistance [98].
6–7. MM proliferation [50].
8. Enhanced LFA-1, ICAM-1, VCAM-1, and VLA-4 (MM) and ICAM-1 (BM-MSCs), increased binding of MM to BM-MSCs and further IL6 secretion [54].
1. Natalizumab: anti-α4 integrin (NCT00675428).
2. LFA878: LFA-1 inhibitor (preclinical studies) [41].
3. Tocilizumab: anti-IL6R [57].
4. BHQ880: anti-DKK1 [58].
5. LINC00461 knockdown (preclinical studies) [98].
6. Tabalumab: anti-BAFF [59].
7. APRIL-based CARs target BCMA or TACI [52].
8. Anti- TNFα. However, these drugs in other inflammatory conditions increase the risk of MM [56].
Osteoclast/osteoblast imbalance1. MIP1α and MIP1β (MM).
2. RANKL (osteocytes)/RANK (osteoclasts).
3. MM induce RANKL and IL6 secretion by BM-MSCs.
4. VLA-4 (MM)/VCAM-1 (osteoblasts and BM-MSCs).
1. Osteoclast activation [63,64], IL6 secretion [65], CHSY1 up-regulation, Notch signaling, MM survival, recruitment of osteoclast precursors [66].
2–3. Osteoclast activity [67,68].
4. RUNX2 decreased activity, decreased osteoblast differentiation [72], decreased OPG secretion, osteoclast formation and bone degradation [73].
1-2-3. Amino-bisphosphonates that inhibit osteoclast activity [69].
2–3. Denosumab: anti-RANKL [70]
4. Natalizumab: anti-α4 integrin (NCT00675428).
4. BHQ880: anti-DKK1 [75].
Angiogenesis in the vascular niche1. VEGF production (MM).
2. EGFR-2, Tie2/Tek, β3-integrin and endoglin in MM endothelial cells.
3. MM cells induce HGF, VEGF and IL8 secretion in BM-MSCs.
4. IGF1 and IL6 secretion by MM endothelial cells.
1. Angiogenesis [82].
2. Enhanced MM cell interaction with new blood vessels and further dissemination [83].
3. Neovascularization [89].
4. MM growth, enhanced MM production of VEGF, PDGF, Ang-1, HGF, and IL1. Enhanced angiogenesis [90].
1. Amino-bisphosphonates are anti-angiogenic [69,99].
1–3. Bevacizumab: anti-VEGF [92,93].
2. Derivatives of quinolone and quinazoline inhibit VEGFRs, EGFR, and PDGFR [94,95].
4. Immunomodulators [96,97].
Effector CD8 T cells1. CXCR4 (MILs)/CXCL12 (BM-MSCs).
2. CM phenotype of MILs.
3. PD-1, CTLA-4, LAG-3, or TIGIT (T cells) with PD-L1, CD80/CD86, MHC-II, and CD155 (MM).
4. TIGIT expression on T cells in MM [100].
1. Trafficking of MILs to the BM [101].
2. Enhanced CR in patients [101].
3. Inhibition of T cell activity [102,103]
4. Dysfunctional T cells with decreased proliferation and cytokine production [100].
1. Administer MILs with enhanced CXCR4 expression that has shown efficacy in CAR-T cells [104].
2. Addition of PI3K inhibitors during the production of MILs [105].
3. ICI treatments targeting others than PD-1/PD-L1 due to their toxicity in MM [106].
4. TIGIT inhibition [100].
CD4 conventional T cells1. Reduced CD4/CD8 ratio, lower number of CD4 T and Th2 cells in MM [107].
2. IL6 secretion inhibits polarization of naïve T cells into Th1 cells [108].
3. GPRC5D (MM)/CD4 T cells [109].
1–2. Tumor escape to immune surveillance [108].
3. Inhibition of CD4 T-cell anti-MM activity.
1. Optimization of CD4/CD8 ratio in cellular immunotherapy products [110,111].
2. Tocilizumab (anti-IL6R).
3. Bispecific antibody against GPRC5D. (talquetamab) enhances anti-MM activity of CD4 T cells [109].
T-reg cells1. Increased T-regs in the BM of MM [112,113].
2. IL10 and TGFβ secretion by T-regs.
3. CTLA-4 and ICOS expression in T-regs.
4. ICOS (T-reg)/ICOSL (MM) [114].
5. GPRC5D (MM)/T-regs [109].
1. Shorter time to progression [112,113].
2. Interruption of CD4 T cell-mediated generation of CD8 T cell responses [115]
3. T-reg suppressive activity [116].
4. Generation of functional T-regs [114].
5. Inhibition of CD4 conventional and T-reg activity.
1–2. Optimized MIL product with lower number of T-regs induces CR [101].
2. Transient T-reg depletion [117].
3, 4. Inhibition of T-regs with anti-ICOSL MoAb [114].
5. Talquetamab enhances anti-MM activity of T-reg cells by themselves [109].
Th17 cells1. IL6 induces IL21 that with TGFβ induces Th17 differentiation [118].1. MM growth [119], osteoblast cell death [120], osteoclasts activation, tumor growth and MBD [119].Thalidomide normalizes the ratio of Th17 and T-reg cells in PB [121]. Anti-IL17 Ab show anti-MM activity [122].
Age in T cellsHigh number of immunosenescent T cells (CD57, KLRG1, CD160, CD28, PD1low, and CTLA4low) [123].Enhanced by chemotherapy [124] and ICI treatments [125].Addition of PI3K inhibitors [105], IL15 [126] and sestrins inhibition [127] during the production of the immunotherapy product.
NK cells1. MM cells downregulate NKG2D and NKp80 on NK cells [128].
2. PDL1 (MM)/PD1 (NK cells) [129].
3. BM-MSCs-derived IL6.
4. Tumor-derived IL1β in MDSCs.
5. Increased CXCL9 and CXCL10, decreased CXCL12, down-regulation of CXCR3 on NK cells.
6. CD56bright NK cells highly activated in BM and PB [130].
1. Inhibition of NK activity [128].
2. Inhibition of NK activity [129].
3. NK inhibition [131], PD-L1 on MM cells, impacting the NK and T cell activity [132,133].
4. NK inhibition [134].
5. Driving of NK cells outside the BM [135].
6. Additional markers to characterize a possible angiogenic activity of CD56bright NK cells.
1-2-3-4-5: Combination of IMiDs and MoAb enhance endogenous NK cell activity and ADCC of NK cells.
BiKEs/TRiKEs redirect endogenous NK cells to tumor cells.
Ab recruiting molecules bind tumor-associated antigens with endogenous IgG inducing NK-mediated ADCC.
ALT-803: IL-15 superagonist that stimulates NK cells and T cells.
CAR-NKs targeting SLAMF7, CD138 or NKG2D ligands on MM [136,137].
6. Previous selection of in vitro expanded CD56dim NK cells.
Regulatory B cellsMM cells promote B-reg cell survival and their accumulation in the BM.1. IL10 secretion of B-reg cells inhibits CD4 T cell differentiation into Th1 and Th17 cells, and favors polarization into T-regs [138].
2. B-regs avoid NK-ADCC in MM [139].
Strategies to target B-reg cells have not been described yet. Novel research to decipher cellular interactions with B-regs and how B-regs exert their suppressive activity is required.
TAMs1. CXCL12 (MM and BM-MSCs)/CXCR4 (monocytes).
2. M2 macrophage immunosuppresion through IL6, IL10, IL8, TNFα, CD206, CD163, CCL2.
3. CD47 (MM)/SIRPα (macrophages).
1. Monocytes recruitment and M2 polarization in BM [140].
2. MM proliferation and progression [141,142].
3. Immune checkpoint resulting in a “don’t eat me” signal in M2 macrophages and immune evasion [143].
1. AMD-3100: CXCR4 inhibitor (preclinical studies) [140].
2. Clodronate liposome to deplete resident M2 macrophages in BM (preclinical studies) [144].
2. Anti-CSF1R to reprogram TAMs to promote M1 phenotype (preclinical studies) [145].
3. Antibodies anti-CD47 (SRF231: NCT03512340 and AO-176: NCT04445701).
3. SIRPα-IgG1 Fc fusion proteins (TTI-621: NCT02663518 and TTI-622: NCT03530683).
MDSCs1. IL10, CCL5, MIP-1 or IL6 from MM cells generate MDSCs
2. ARG1, ROS, COX2, iNOS, IL6, IL10 and IL18 (MDSCs)
1–2. Inhibit immune responses, induce T-regs, promote angiogenesis and differentiate into osteoclasts [146].1. Daratumumab: anti-CD38 (dual targeting of MM cells and MDSCs) [147]
2. Tagraxofusb: CD123-targeted agent [148]
ECM: extracellular matrix; BM-MSCs: Bone marrow mesenchymal stromal cells. TAMs: tumor-associated macrophages. MDSCs: myeloid-derived suppressor cells. MM: multiple myeloma. BM: bone marrow. PB: peripheral blood. MILs: marrow-infiltrating lymphocytes. ICI: immune checkpoint inhibition. MBD: myeloma bone disease. MoAb: monoclonal antibody. CM: central memory. CR: complete response. ADCC: antibody-dependent cell cytotoxicity. Ang-1: Angiopoietin 1; APRIL: A Proliferation-Inducing Ligand; ARG-1: Arginase 1; BAFF: B-Cell Activating Factor; BCMA: B Cell Maturation Antigen; bFGF: basic Fibroblast Growth Factor; CCL2: C-C motif chemokine Ligand 2; CCL5: C-C motif chemokine Ligand 5; CHSY1: Chondroitin Sulfate Synthase 1; COX2: cyclooxygenase 2; CTLA-4: Cytotoxic T-Lymphocyte-associated Antigen 4; CXCL9: C-X-C motif chemokine Ligand 9; CXCL 10: C-X-C motif chemokine Ligand 10; CXCL12: C-X-C motif chemokine Ligand 12; CXCR3: C-X-C motif chemokine Receptor 3; CXCR4: C-X-C motif chemokine Receptor 4; DKK1: Dickkopf1; EGFR-2: Epidermal Growth Factor Receptor 2; GPRC5D: G Protein–coupled Receptor, class C, group 5, member D; HGF: Hepatocyte Growth Factor; ICAM-1: Intercellular Adhesion Molecule 1; ICOS: Inducible T-cell COStimulator; IGF-1: Insulin-like Growth Factor 1; IL: interleukin; iNOS: inducible Nitric Oxide Synthase; KLRG1: Killer cell Lectin-like Receptor subfamily G member 1; LAG-3: Lymphocyte Activation Gene 3; LFA-1: Lymphocyte Function-associated Antigen 1; MHC-II: Major Histocompatibility Complex class II; MIP1α: Macrophage Inflammatory Protein 1 α; MIP1β: Macrophage Inflammatory Protein 1 β; NFkB: Nuclear Factor kappa-light-chain-enhancer of activated B cells; NKG2D: Natural Killer Group 2 member D; OPG: Osteoprotegerin; PD-1: Programmed Death 1; PD-L1: Programmed Death-Ligand 1; RANK: Receptor Activator of Nuclear Factor k B; RANKL: Receptor Activator of Nuclear Factor k B Ligand; ROS: Reactive Oxygen Species; RUNX2: Runt-related transcription factor 2; SIRPα: Signal Regulatory Protein α; TACI: Transmembrane Activator and CAML (Calcium-Modulator and Cyclophilin Ligand) Interactor; TGFβ: Transforming Growth Factor β; TIGIT: T cell Immunoreceptor with Ig and ITIM domains; TNFα: Tumor necrosis factor α; VCAM-1: Vascular Cell Adhesion Molecule 1; VEGF: Vascular Endothelial Growth Factor; VLA-4: Very Late Antigen-4.
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Hervás-Salcedo, R.; Martín-Antonio, B. A Journey through the Inter-Cellular Interactions in the Bone Marrow in Multiple Myeloma: Implications for the Next Generation of Treatments. Cancers 2022, 14, 3796. https://doi.org/10.3390/cancers14153796

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Hervás-Salcedo R, Martín-Antonio B. A Journey through the Inter-Cellular Interactions in the Bone Marrow in Multiple Myeloma: Implications for the Next Generation of Treatments. Cancers. 2022; 14(15):3796. https://doi.org/10.3390/cancers14153796

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Hervás-Salcedo, Rosario, and Beatriz Martín-Antonio. 2022. "A Journey through the Inter-Cellular Interactions in the Bone Marrow in Multiple Myeloma: Implications for the Next Generation of Treatments" Cancers 14, no. 15: 3796. https://doi.org/10.3390/cancers14153796

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Hervás-Salcedo, R., & Martín-Antonio, B. (2022). A Journey through the Inter-Cellular Interactions in the Bone Marrow in Multiple Myeloma: Implications for the Next Generation of Treatments. Cancers, 14(15), 3796. https://doi.org/10.3390/cancers14153796

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