Next Article in Journal
Effects of Serum Lipids on the Long-Term Prognosis of Ampullary Adenocarcinoma Patients after Curative Pancreatoduodenectomy
Next Article in Special Issue
Molecular Crosstalk between Chromatin Remodeling and Tumor Microenvironment in Multiple Myeloma
Previous Article in Journal
Caregiver Burden in Distance Caregivers of Patients with Cancer
Previous Article in Special Issue
Targeting CAM-DR and Mitochondrial Transfer for the Treatment of Multiple Myeloma
 
 
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Treating Multiple Myeloma in the Context of the Bone Marrow Microenvironment

1
Department of Internal Medicine, Mayo Clinic, Rochester, MN 55902, USA
2
Division of Hematology, Department of Internal Medicine, Mayo Clinic, Rochester, MN 55902, USA
3
Division of Hematology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02120, USA
*
Author to whom correspondence should be addressed.
Curr. Oncol. 2022, 29(11), 8975-9005; https://doi.org/10.3390/curroncol29110705
Received: 18 October 2022 / Revised: 8 November 2022 / Accepted: 18 November 2022 / Published: 21 November 2022

Abstract

:
The treatment landscape of multiple myeloma (MM) has evolved considerably with the FDA-approval of at least 15 drugs over the past two decades. Together with the use of autologous stem cell transplantation, these novel therapies have resulted in significant survival benefit for patients with MM. In particular, our improved understanding of the BM and immune microenvironment has led to the development of highly effective immunotherapies that have demonstrated unprecedented response rates even in the multiple refractory disease setting. However, MM remains challenging to treat especially in a high-risk setting. A key mediator of therapeutic resistance in MM is the bone marrow (BM) microenvironment; a deeper understanding is necessary to facilitate the development of therapies that target MM in the context of the BM milieu to elicit deeper and more durable responses with the ultimate goal of long-term control or a cure of MM. In this review, we discuss our current understanding of the role the BM microenvironment plays in MM pathogenesis, with a focus on its immunosuppressive nature. We also review FDA-approved immunotherapies currently in clinical use and highlight promising immunotherapeutic approaches on the horizon.

Graphical Abstract

1. Introduction

Multiple myeloma (MM) is the second most common hematologic malignancy in high-income countries [1]. MM is preceded in virtually all cases by the asymptomatic precursor states monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) (Figure 1), as shown by population-based studies published in 2009 [2,3]. Survival in MM has improved significantly over the past decades with the use of autologous stem cell transplantation (ASCT), as well as novel agents that treat MM in the context of the BM microenvironment (Figure 2) [4]. However, MM is still mostly incurable outside of allogeneic stem cell transplant which, despite significant treatment-related toxicity, remains the only treatment that can enable long-term progression-free survival (PFS) or potentially even cure carefully selected patients with high-risk MM [5]. Similar to how long-lived plasma cells are critically dependent on their ability to traffic to pro-survival niches within the BM and other lymphoid organs [6], it has become increasingly clear that MM cells rely on the BM microenvironment for survival, proliferation, and drug resistance [7,8]. This reliance on the BM microenvironment occurs early on during the MGUS phase as suggested by studies showing progressive growth in MGUS cells xenotransplanted in humanized mice that express several human genes essential for the growth of human cells [9]. Additionally, a recent whole-genome analysis of paired samples from a small number of non-high-risk SMM cases that progressed to MM revealed that, in some cases, the SMM clone may be genomically indistinguishable from MM [10]. This further suggests that the BM microenvironment or tumor-extrinsic signals may play a dominant role in influencing MM growth and progression. This MM-permissive BM microenvironment includes noncellular components (e.g., extracellular matrix proteins, growth factors, cytokines, extracellular vesicles), which are produced or influenced by the cellular compartments comprising BM mesenchymal stromal cells, immune cells, osteoblasts/osteoclasts, and BM endothelial cells [8].
Figure 2 summarizes the timeline of FDA approvals for therapies for multiple myeloma.

2. The Role of the Tumor Microenvironment in the Initiation of the Myeloma Clone

There are two types of largely mutually exclusive primary genetic events that give rise to the MM clone, each accounting for roughly half of myeloma cases: (1) hyperdiploidy, hypothesized to result from chromosome segregation errors occurring during rapid germinal center proliferation, and (2) IgH translocation, which is a result of the error-prone class switch recombination (CSR) process that activated B cells undergo [11]. Importantly, data suggests that MM is initiated by mutations associated with T cell-dependent B-cell activation [11]. T cell-dependent B-cell activation results in the activation of the co-stimulatory CD40-CD40L pathway within B cells [12,13], as well as release of T-cell cytokines IL4, IL21, and IL6 [14,15,16]. IL6 is a well-known activator of B cells and potent stimulator of B cell, plasma cell, and MM proliferation and survival [17]. B cells that undergo T cell-dependent activation rapidly proliferate and form germinal centers within lymphoid organs [18,19]. Within these germinal centers, activated B cells undergo rounds of division whereby a large repertoire of high-affinity antibodies is made through CSR and somatic hypermutation (SHM) [20]. CSR requires the formation of double-strand breaks and can therefore give rise to IgH translocations when aberrant recombination with other genomic regions occur [11]. The MM clone then homes into the BM mediated by the interaction of the MM receptor CXCR4 with the chemokine SDF1α [21]. Within the BM microenvironment, MM interacts with the extracellular matrix (ECM), which consists of proteins such as fibronectin, collagen, osteopontin, hyaluronan, and laminin; and cellular compartments including the BM stromal cells (BMSCs) [7]. Direct contact of MM cells with BMSCs activates downstream pathways such as MAPK, NOTCH, and Pi3K, which results in the secretion of pro-survival cytokines [7]. Examples include IL6, which facilitates MM survival, proliferation, migration, and drug resistance through the MEK/MAPK, JAK/STAT, and PI3K/Akt pathways. Other cytokines include the B-cell activating factor (BAFF) and a proliferation inducing ligand (APRIL), both of which promote MM proliferation via MAPK and NFκB, TNFα, insulin-like growth factor (IGF), hepatocyte growth factor (HGF), basic fibroblast growth factor (bFGF), and vascular endothelial growth factor (VEGF) [7]. Progression from MGUS to MM is then a multistep complex process involving further acquisition of secondary genetic events that confer a selection advantage, as well as immune modifications in the tumor microenvironment [22].

3. The Role of the Immunosuppressive Microenvironment in the Progression of MM

One key step in tumorigenesis is the ability of cancer to evade immune surveillance, the process by which a competent immune system recognizes and eliminates tumor cells [23]. MM clones and subclones that harbor mutations that allow them to escape immune destruction are selected for growth within the BM microenvironment [24]. Additionally, MM cells maintain a highly immunosuppressive BM microenvironment by promoting the expansion of myeloid-derived suppressor cells (MDSCs), tumor-associated M2-like macrophages (M2 TAMs), N2 neutrophils, regulatory T cells (Tregs), regulatory B cells (Bregs), and plasmacytoid dendritic cells (pDCs) [8,25].
The immunosuppressive MM BM microenvironment consists of myeloid-derived suppressor cells (MDSCs), tumor-associated M2-like macrophages (M2 TAMs), N2 neutrophils, regulatory T cells (Tregs), regulatory B cells (Bregs), and plasmacytoid dendritic cells (pDCs) [8]. Multiple immunotherapeutic approaches have been developed including antibody-based therapies (e.g., monoclonal antibodies, bispecific antibodies) and cellular therapies (e.g., CAR T cells, CAR-NK cells, CAR-M) to target MM within the context of the BM. Despite high response rates in patients treated with multiple prior lines of therapy, one limitation to current immunotherapeutic approaches is the lack of durability and the high rates of relapse. Studies aimed at uncovering the mechanism of MM immune evasion and effector cell exhaustion are currently underway.

3.1. Regulatory T Cells (Tregs)

Tregs are a subset of CD4+ T cells that express forkhead box P3 (FoxP3) and function to suppress immune response to maintain self-tolerance [26]. FoxP3 is the main transcription factor enabling the function of Tregs, and Tregs are immunophenotypically characterized by CD3+CD4+CD25hiCD127loFoxP3+ [27]. In the context of the immunosuppressive MM BM microenvironment, Tregs inhibit MM-specific T-cell effector functions through direct cell-to-cell contact and the secretion of IL10, TGFβ, and IL35, as well as cytolytic granzymes and perforins, to inhibit and/or kill immune effector cells [28,29,30]. TGFβ is not only immunosuppressive but under the right conditions and together with IL2, has been shown to be able to induce the expression of FoxP3 in effector cells resulting in their functional conversion to Tregs [31]. In vitro studies have also shown that direct contact with MM cells is able to induce the development of CD4+CD25+FoxP3+ Tregs from an initial population of CD4+CD25FoxP3 cells, mediated by an inducible T-cell co-stimulator (ICOS) on T cells and their ligands (ICOS-L) expressed on MM cells [32]. Notably, one study showed that a lenalidomide and dexamethasone combination is able to reduce ICOS-L expression on MM cells and inhibit Treg differentiation measured by decreased FoxP3 expression [33]. However, other studies have reported conflicting results that lenalidomide increases Treg frequency in patients with MM and chronic lymphocytic leukemia [34,35,36,37]. This discrepancy in response to lenalidomide treatment may be dose- and time-dependent where short-term treatment induces Treg but prolonged treatment with increasing doses of lenalidomide inhibits Tregs [34,35]. Another potential explanation could be due to IMiD’s ability to downregulate CXCR4 expression on Tregs [38]. CXCR4-expressing Tregs are attracted to the MM BM microenvironment by cytokines such as stromal-derived-factor-1ɑ (SDF-1α), CXCR4 ligand [38]. Downregulation of CXCR4 may therefore allow Tregs to leave the BM and accumulate within the peripheral blood. Other anti-MM agents such as dexamethasone, cyclophosphamide, and daratumumab have also been shown to induce Treg apoptosis [33,39,40,41,42,43,44].
Indoleamine (IDO) is a cytosolic enzyme that degrades tryptophan into kynurenine (KYN). IDO-mediated KYN production promotes Treg development, stabilization, and activation, while suppressing effector T cells [45,46]. KYN is overexpressed in the serum and bone marrow of patients with MM (compared to healthy controls) and also higher in patients with ISS stage II/III disease (compared to ISS stage I) [46]. IDO was found to be expressed by CD138+ MM cells, as well as MM patient-derived BMSCs that were stimulated with IFNγ [46]. High IDO and KYN expression correlated with increased Treg accumulation with the MM BM microenvironment [46]. Conversely, inhibition of IDO with D,L-1-methyl-tryptophan inhibited MM-mediated Treg expansion and promoted T helper type 1 (Th1) differentiation [46]. Engagement of programmed cell death 1 (PD1) on the surface of Th1 cells by PD1 ligand (PDL1)-overexpressing cells or coated beads can also induce Tregs in vitro [47,48]. A proliferation-inducing ligand (APRIL), which is highly secreted by myeloid precursor cells (e.g., megakaryocytes, eosinophils, monocytes) and osteoclasts within the MM BM microenvironment [49], canonically binds B-cell maturation antigen (BCMA) on the MM-cell surface to drive survival and proliferation, has also been shown to bind a transmembrane activator, calcium modulator, and cyclophilin ligand interactor (TACI) on Tregs to drive MM-mediated Treg differentiation, proliferation, and survival [50,51].
The role of Tregs in MM pathogenesis and progression remains unclear, and conflicting studies have shown increased [29,52,53,54,55], decreased [36,56], or unchanged [57,58] Treg frequency in patients with MM. This lack of consistency is likely due to differences in the compartment studied (peripheral blood vs bone marrow), different immunophenotypic definitions of Tregs (CD4+FoxP3+, CD4+CD25hi, CD4+CD25+FoxP3+, CD4+CD25+CD127), and interpatient tumor heterogeneity. The compartment matters as one study showed that Tregs are enriched in the peripheral blood (but not BM) of patients with treatment-naïve MM when compared to MGUS and controls [59]. The same study, however, did show that activated and memory Tregs were enriched in both the peripheral blood and BM of patients with treatment-naïve MM but that resting Tregs were significantly higher in controls [59]. Although this corresponded with increased terminally differentiated CD8+ effector cells seen in patients with treatment-naïve MM and increased central memory CD8+ T cells in controls, the study did not show a difference in the in vitro suppressive capacity of Tregs isolated from treatment-naïve MM compared to controls [59]. Specifically, Tregs were isolated from MM and controls and co-cultured with CD3/CD28 bead-activated PBMCs, and flow cytometry was used to analyze markers of activated T cells (i.e., CD69 and CD154 expression on CD4+ and CD8+ T cells). MM-derived Tregs did not significantly decrease the proportion of CD69 or CD154-expressing activated T cells when compared with healthy donor-derived Tregs [59].
Finally, studies comparing the frequency of Tregs in the BM versus peripheral blood of patients with MM have also reported inconsistent results, with some studies reporting higher frequencies in the MM BM [59,60,61] and others reporting similar peripheral blood and BM Treg frequencies [52,55].

3.2. Plasmacytoid Dendritic Cells (pDCs)

Plasmacytoid dendritic cells (pDCs) are a specialized subset of CD123 and CD303 co-expressing dendritic cells derived from BM hematopoietic stem cells [62]. Physiologically, pDCs are part of innate immunity and regulate anti-viral responses [62]. Upon stimulation by viral RNA and DNA, pDCs produce IFNγ and differentiate into professional antigen-presenting cells to stimulate T cells of the adaptive immune system [62]. pDCs eventually leave the BM and migrate directly into primary lymphoid organs and T cell-rich areas of secondary lymphoid tissues where they reside normally [62]. However, it has been reported in a number of human tumors that malignant cells recruit pDCs to the tumor microenvironment to help with immune tolerance [63]. This preferential accumulation of pDCs within the BM (as opposed to peripheral blood) is similarly seen in MM [64]. Compared to healthy donor-derived BM samples, MM patient-derived BM samples had higher frequencies of pDCs, and while no significant difference in pDC number was observed between healthy BM vs peripheral blood, an increased number of pDCs were noted in MM BM vs MM peripheral blood [64]. Importantly, in vitro co-cultures show that pDCs isolated from MM BM were able to induce proliferation and confer bortezomib resistance in MM cell lines [64]. Additionally, pDCs isolated from the MM BM showed significantly impaired ability to trigger T-cell proliferation (assessed by 3H-thymidine incorporation assay) when compared to normal pDCs [64].
pDCs highly express PDL1, which is further enhanced by pDC-MM interaction, and this leads to inhibition of T- and NK-cell function [65]. Consistent with this, blockade of the PDL1-PD1 interaction with the anti-PDL1 antibody was able to restore MM-specific cytotoxic T-cell and NK-cell activity [65]. MM-derived pDCs were also able to trigger MM proliferation and confer drug resistance to bortezomib in vitro [64]. Mechanistically, pDC-MM contact stimulates the secretion of IL10, VEGF, CD40L, IL8, IL15, IL6, and MCP1 [64]. This growth-promoting effect can be abrogated by disrupting NF-κB through the inhibition of the B-cell activating factor (BAFF)/APRIL and receptor activator of NF-κB (RANK)/RANKL signaling [64]. Additionally, because pDCs strongly expresses CD38, daratumumab induces strong depletion of pDCs [66].

3.3. Myeloid-Derived Suppressor Cells (MDSCs)

Myeloid-derived suppressor cells (MDSCs) are a heterogeneous population of immature myeloid cells that have been shown to accumulate in both the peripheral blood and BM of patients with MM [67]. There are two types of MDSCs: monocytic MDSC (M-MDSC) and polymorphonuclear MDSC (PMN-MDSC) that are distinguished by CD14 expression [68]. M-MDSCs (CD11b+CD14+CD33+HLA-DRlow/−), in particular, are enriched in patients with newly diagnosed and relapsed MM compared with patients in remission, and high levels of M-MDSCs have been found to correlate with MM progression and treatment resistance [69]. Functionally, MDSCs induce T-cell apoptosis by producing nitric oxide and suppress T-cell function by producing reactive oxygen and nitrogen species, as well as deplete the microenvironment of L-arginine and L-cysteine, which are used to produce the CD3ζ-chain, a component of the T-cell receptor [70,71,72,73].
In vitro co-culture experiments show that exposure of peripheral blood mononuclear cells (PBMCs) obtained from healthy donors to direct contact with MM cells, conditioned media from MM cell lines, and plasma from newly diagnosed patients can induce the development of MDSCs [69,74,75]. The C-C motif chemokine ligand 5 (CCL5) and macrophage migration inhibitory factor (MIF) have recently been found to be key soluble mediators of MDSC induction and are secreted by MM cells [76]. The same study found that both lenalidomide and pomalidomide were able to decrease MM expression of CCL5 (through cereblon-dependent pathways) and MIF (through cereblon-independent pathways) [76]. Both IMiDs were also able to decrease expression of the C-C motif chemokine receptor 5 (CCR5) and induce interferon regulatory factor 8 (IRF8) expression, a negative regulator of differentiation towards MDSCs [76].

3.4. Cancer-Associated Fibroblasts (CAFs)

Cancer-associated fibroblasts (CAFs) are a heterogeneous population of CD45 BM stromal cells expressing different levels of fibroblast specific protein 1 (FSP1), alpha smooth muscle actin (αSma), and fibroblast activating protein (FAP) [77,78]. CAFs have recently been shown to mediate MM proliferation and therapeutic resistance through the production of various cytokines (e.g., IL6, TGFβ), chemokines (e.g., SDF-1), and pro-inflammatory and pro-angiogenic factors (e.g., VEGF) [77,78]. Consistent with this, BM CAFs are enriched in patients with newly-diagnosed and relapsed MM compared to patients with MGUS or non-MM controls [78]. In vivo studies with syngeneic 5T33MM and xenograft mouse models show that MM cells are able to induce CAF proliferation [78]. Direct contact between MM cells and CAFs through CXCL12/CXCR4 and other integrins is necessary to facilitate the tumor-promoting functions of CAFs [77]. Strategies aimed at depleting CAFs using monoclonal antibodies and CAR T cells are currently being studied preclinically and will be discussed later.

3.5. Tumor-Associated M2-like Macrophages (M2 TAMs)

Mature macrophages are identified by the surface markers CD16, CD68, CD115, CD163, and CD312, and represent a major aspect of the innate immune system [79]. Beyond phagocytosis of pathogens and apoptotic cells, macrophages have both tumor promoting and tumor killing effects depending on environmental cues [80]. Two flavors of macrophages exist depending on function: (1) M1 macrophages, which are classically activated by interferon-γ (IFNγ) or lipopolysaccharide (LPS), facilitate tumor killing through phagocytosis, the release of nitric oxide and reactive oxygen species, as well as proinflammatory cytokines (i.e., IL1, IL6, IL8, IL12, TNFα) [80,81,82], and (2) the IL4 dependent alternatively-activated M2 macrophages, which are anti-inflammatory [83,84]. M2 macrophages support tumor growth by secreting vascular endothelial growth factor (VEGF), transforming growth factor-β (TGFβ), IL10, and also through expression of PD-L1 [83,84,85].
Phenotypically and functionally similar to M2 macrophages are CD163 and CD206 expressing tumor-associated M2-like macrophages (M2 TAMs) [86]. TAMs originate from peripheral blood monocytes that infiltrate into the tumor microenvironment in response to cytokines such as VEGF, colony stimulating factor-1 (CSF1), CXC motif chemokine ligand-12 (CXCL12) and various CC motif chemokine ligands (CCL) such as CCL2 [87,88]. TAMs make up about 10% of the BM of patients and have been found in higher proportions in patients with aggressive disease [89,90,91]. In vitro studies have recently shown that the IL10 secretion by MM cells polarized macrophages towards M2 phenotype and that inhibition of IL10 signaling with an IL10 receptor blocking antibody resulted in reversal of the M2 phenotype and loss of TAM-mediated MM proliferation and drug resistance [92]. Functionally, TAMs support MM proliferation (by secreting IL6), angiogenesis (by secreting VEGF, CCLs, matrix metalloproteinases (MMPs)), and immunosuppression (by secreting IL10, TGFβ, indoleamine 2,3-dioxygenase (IDO) and inhibiting IL12 and TNFα production) in the tumor microenvironment [93,94].
Other strategies to target TAMs in the MM BM microenvironment include (1) depleting TAMs by direct killing with clodronate-liposome or inhibiting chemokine signaling (e.g., CXCL12-CXCR4, CCL2-CCR2 to interrupt monocyte recruitment into the BM [95,96,97,98,99], (2) polarizing TAMs towards an M1 phenotype by inhibiting CSF1 receptor signaling or the pro-M2 cytokine macrophage migration inhibitory factor, or by using granulocyte-macrophage CSF (GM-CSF) or the Janus kinase (JAK) 1/2 inhibitor ruxolitinib, both of which have been shown to induce M1 polarization [100,101], and (3) inhibiting the immunosuppressive effects of TAMs [79]. To this end, research into inhibiting IDO to restore T-cell function is currently underway [46].

3.6. N2 Neutrophils

Owing to significant phenotypic and functional overlap between N2 neutrophils and PMN-MDSCs, there has been some confusion on the classification of these cells [102]. In fact, density gradient centrifugation is the only way to phenotypically differentiate TANs from PMN-MDSCs (which end up on the low-density layer) [103]. Unlike T and NK cells, the role of neutrophils in the tumor microenvironment is less clear as tumor-associated neutrophils have been found to possess both anti-tumor (e.g., direct cytotoxicity and inhibition of metastasis) and pro-tumor activity (e.g., promote angiogenesis, stimulate tumor cell migration and invasion, contribute to immunosuppression) [102]. Similar to TAMs, neutrophils maintain functional plasticity and can be alternatively activated in response to microenvironmental cues. Specifically, the presence of TGFβ within the microenvironment polarizes neutrophils towards a protumor phenotype (termed N2 neutrophils), while the presence of interferon-β (IFNβ) results in an antitumor phenotype (termed N1 neutrophils) [102].
Neutrophils isolated from the peripheral blood of patients with newly diagnosed MM have been shown to have a different gene expression profile compared with healthy donor-derived neutrophils [104]. Compared with both healthy donors and MGUS, neutrophils derived from patients with MM had genes dysregulated in FC-γ-R mediated phagocytosis, endocytosis, leukocyte transendothelial migration, chemokine signaling Toll-like receptor pathways, and inositol-phosphate metabolism [104]. Functionally, there is limited data showing that neutrophils derived from both the peripheral blood and BM of patients with MM were able to inhibit T-cell proliferation in a similar fashion to PMN-MDSCs by producing ROS and/or arginase-1 (which depletes L-arginine from the microenvironment) [104,105]. Noteworthy, studies present conflicting results with some showing that neutrophils derived from the peripheral blood of patients with MM did not have an increased T-cell inhibitory effect compared with peripheral blood neutrophils from healthy donors [105].

3.7. Regulatory B Cells (Bregs)

Bregs are a subset of B cells characterized by CD19+CD24highCD38high that, similar to Tregs, secrete IL10, IL35, and TGFβ and have been implicated in MM progression [106,107,108]. Bregs have been found to preferentially accumulate in the BM (as opposed to peripheral blood) of patients with MM [107]. Consistent with this, Bregs isolated from the BM of patients with MM were dependent on MM cells for survival in vitro as removal of CD138+ MM cells from the BM mononuclear cell culture resulted in Breg apoptosis as measured by the annexin V/propidium iodide apoptosis assay [107]. MM-derived Bregs were found to highly express TACI and the addition of APRIL in vitro increased the frequency of IL10-producing Bregs [50]. Functionally, a greater percentage of Bregs isolated from the BM were IL10 producing when compared to peripheral blood Bregs, and BM Bregs were able to inhibit elotuzumab associated antibody-dependent cellular cytotoxicity (ADCC) by NK cells [107].
Bregs also express PDL1 and CD1d on the cell surface, the latter of which is a nonpolymorphic MHC class I-like molecule found on antigen-presenting cells that facilitates the presentation of glycolipid antigens to natural killer T (NKT) cells, a process that is essential for the development of invariant NKT cells [106]. CD1d is also highly expressed by MM cells, especially during early stages of disease progression and MM cells can “hijack” this normally proinflammatory antigen presenting system to instead disrupt iNKT cell function [109]. MM cells secrete GM3 ganglioside, which together with the high levels of CD1d expression in the BM microenvironment, results in the formation of the CD1d/GM3 complex, which binds to the invariant T-cell receptor of iNKT resulting in iNKT deregulation, loss of IFNγ secretion, and immune evasion [109].

3.8. Impaired Immune Effector Killing in MM

The functional sequelae of the immunosuppressive BM microenvironment are diminished effector T-cell survival, proliferation, and function, evidenced by multiple CD4 and CD8 T-cell signaling defects (e.g., downregulation of CD28, CD152, CD3ζ, p56lck, ZAP-70, and PI3K; upregulation of exhaustion markers) in patients with advanced stage MM [110]. Additionally, the MM BM microenvironment is enriched for coinhibitory molecules (e.g., PDL1 on MM cells, Galectin-3 and HLA-DR on MM cells, Galectin-9 in the MM BM plasma; and corresponding immune checkpoint receptors PD1, LAG3, and TIM3 on T cells) [111,112,113,114,115,116,117,118]. Soluble factors such as IL6 (via JAK2/STAT3 and MEK/ERK signaling), IFNγ (via MyD88/TRAF6 and MEK/ERK signaling), and APRIL (via BCMA binding and MEK/ERK signaling) are found in high abundance within the MM BM microenvironment and have been implicated in promoting PDL1 expression [113,114,115,119]. In spite of this, clinical trials studying monotherapy with PD1/PDL1 inhibitors have yielded lackluster results, and this is likely due to the highly dysfunctional MM T cells, which coexpress T-cell immunoglobulin mucin-3 (TIM3) and lymphocyte-activation gene 3 (LAG3), and a combined blockade of multiple checkpoint pathways may be needed [116,117,120].

4. The Era of Immunotherapy in MM

Cancer immunotherapy is a treatment that enhances the body’s immune system to prevent, control, and kill cancer cells. With increasing clinical use and experience, the advantages of immunotherapy over traditional anti-tumor therapy are apparent. These include the potential for higher specificity, potency, applicability (as killing does not hinge on the presence of specific mutations), and persistence, with the additional benefit of more tolerable side effects [121]. Several immunotherapies are already in routine clinical use with many others currently under active investigation. Bolstered by unprecedented clinical efficacy, we are starting to see a shift in focus away from molecularly targeted therapy towards developing immunotherapies for MM.

5. Chimeric Antigen Receptor T (CAR T)-Cell Therapy

Chimeric antigen receptor T (CAR T)-cell therapy, and in particular CD-19 CAR T-cells, has recently been proven to be highly effective in the treatment of acute lymphoblastic leukemia (ALL) and non-Hodgkin lymphoma (NHL) (e.g., tisagenlecleucel/Kymriah, axicabtagene ciloleucel/Yescarta, lisocabtagene/Breyanzi, brexucabtagene/Tecartus) [122,123,124,125,126]. Compared with ALL and NHL, CAR T research in MM is still in the early stages with the first MM-specific BCMA CAR developed less than a decade ago [127]. A summary of CAR T-cell trials is detailed in Table 1. There are currently two FDA-approved BCMA-CARs for patients with heavily pretreated relapsed or refractory MM: idecabtagene/Abecma, which showed an overall response rate (ORR) of 73% with median progression free survival (PFS) of 12.1 months at target dose of 450 × 106, and ciltacabtagene/Carvykti (bi-epitope CAR containing 2 BCMA-targeting domains), which had an ORR of 97% and median PFS was not reached (Table 1) [128,129]. However, unlike CAR T-cell therapy for ALL or diffuse large B-cell lymphoma (DLBCL), which has the potential to induce durable remissions, the majority of patients with MM treated with BCMA-CARs relapse within two years despite favorable response rates [130].

5.1. Mechanisms of Resistance to CAR T-Cell Therapy

Several mechanisms of CAR T-cell resistance were proposed including BCMA antigen escape and heterogeneity, as well as short-term T-cell persistence due to activation-induced cell death (AICD), poor T-cell expansion, and terminal effector T-cell differentiation and exhaustion [131,132]. Intra-tumoral BCMA heterogeneity can lead to the selection and proliferation of clones with low/no BCMA expression as MM cells with high BCMA expression are preferentially killed [133,134,135]. This is consistent with studies reporting loss of BCMA upon disease relapse after the first CAR T-cell infusion [136,137,138,139]. Antigen escape can occur because of permanent antigen loss from alternative splicing or heterozygous deletion of chromosome 16p and concomitant frameshift or missense mutation of the other allele [138,140,141], or reversible antigen loss through trogocytosis (active transfer of target antigen to T cells), increasing the risk of T-cell fratricide and exhaustion [142,143,144]. Additionally, BCMA is actively cleaved from the MM-cell surface by the ubiquitous γ-secretase (GS) complex, which not only decreases the density of antigen on MM cells but also releases a soluble BCMA (sBCMA) fragment that can act as a decoy to inhibit CAR T-cell function [145]. Conversely, small-molecule γ-secretase inhibitors (GSIs) have been shown to stabilize BCMA expression on the cell surface and decrease sBCMA, as well as enhance efficacy of CAR T-cell therapy; a phase I clinical trial (NCT03502577) investigating the combination of GSIs with concurrent BCMA CAR T-cell therapy is currently underway [145]. Notably, epigenetic modulation with all-trans retinoic acid (ATRA) increases BCMA expression on MM cells to improve recognition by BCMA CAR T cells [146]. A combination of ATRA and GSIs showed a synergistic effect compared with a single-agent treatment alone [146].
Another strategy to overcome antigen escape is to employ CAR T cells that concomitantly target multiple antigens using either dual CAR constructs or tandem CARs (i.e., a single CAR construct expressing two single chain variable fragments/scFVs) [147]. Several dual CAR T-cells targeting BCMA/CD19 (NCT04162353), BCMA/SLAMF7 (NCT04156269), BCMA/CD38 (NCT03767751), BCMA/NY-ESO1 (NCT03638206), and CD38/CD19 (NCT03125577) are currently being evaluated in clinical trials (NCT03271632, NCT03473496) (Table 1) [147]. Dual targeting cancer-associated fibroblasts (CAFs) and MM cells is another novel strategy aimed at overcoming CAR T-cell resistance that has demonstrated promising preclinical results [148]. In one study, Sakemura et al. first showed that CAFs isolated from the BM of patients with MM significantly enhanced MM tumor growth both in vitro and in vivo, potently suppressed BCMA CAR T-cell expansion and CAR T-cell degranulation, and significantly altered the CAR T-cell cytokine profile (increased inhibitory cytokines and growth factors: TGFβ, fibroblast growth factor 2 (FGF2), growth-regulated oncogene, IL4, IL5, MCP1, MCP2; decreased effector cytokines: IFNγ, GM-CSF, soluble CD40L, TNFα, TNFβ, macrophage inflammatory protein 1β) [148]. The BM-CAFs were shown to highly express FAP and the signaling lymphocyte activation molecule family-7 (SLAMF7) [148]. The authors then generated dual CAR T-cells targeting MM (via BCMA), as well as CAFs (via either FAP or SLAMF7) and found that both BCMA-FAP and BCMA-SLAMF7 dual targeting CARs were able to overcome CAF-induced CAR T-cell inhibition in an MM-tumor microenvironment (TME) mouse model where the NOD/SCID γ chain-deficient (NSG) mice were simultaneously intravenously injected with both the OPM-2 MM cell line and BM-derived CAFs [148].
Various T-cell directed strategies have emerged to improve CAR T-cell persistence and potency, and these include (1) refinement of the CAR construct to reduce immune rejection, improved binding affinity, and prevention of ligand-independent tonic signaling, (2) development of fourth-generation armored CAR T cells to overcome the immunosuppressive MM BM microenvironment, (3) optimizing T-cell subpopulations prior to CAR T-cell reinfusion (e.g., adjusting the CD4+/CD8+ ratio to 1:1; NCT03430011 and NCT03338972; addition of the PI3K inhibitor bb007 during ex-vivo culture to enrich for memory-like T cells and decrease the proportion of terminally differentiated or senescent T cells; NCT03274219), and (4) using BM-derived T cells (i.e., marrow-infiltrating lymphocytes), which display enhanced memory phenotype and long-term persistence, or allogeneic lymphocytes (i.e., off-the-shelf CAR T cells), which represent a readily available source of T cells without prior exposure to anti-MM therapy [149]. One method to reduce the autoreactivity of allogeneic “off-the-shelf” CAR T cells involves the use of the CRISPR/Cas9 system to knockout the T-cell receptor and MHC class I, coupled with specific insertion of the CAR at the TRAC locus (NCT04244656) [150].
Various microenvironmental-directed strategies to improve CAR T-cell therapy are also currently being investigated, and these include (1) optimization of the dose, timing, and lymphodepleting conditioning regimen used to eliminate immunosuppressive cells and reduce the pool of cells competing for homeostatic cytokines, (2) incorporating CAR T-cell therapy earlier in the disease course prior to adverse changes in the immune microenvironment, and (3) combination therapy with other therapies such as IMiDs and immune checkpoint inhibitors [149].

5.2. Exploiting the Tumor Microenvironment to Overcome CAR T-Cell Therapy-Related Toxicities

Further problems limiting CAR T-cell therapy include toxicity from uncontrolled systemic cytokine levels resulting in cytokine release syndrome (CRS), hemophagocytic lymphohistiocytosis (HLH) and/or macrophage activation syndrome (MAS), and immune effector cell-associated neurotoxicity syndrome (ICANS), as well as on-target/off-tumor effects resulting in B-cell aplasia, neutropenia, and immunosuppression leading to an increased risk of infections [132]. Current treatment of CRS and ICANs is largely supportive with the addition of corticosteroids ± tocilizumab or siltuximab (IL6 antagonists) in severe cases [132]. Treatment of HLH/MAS may require the addition of systemic etoposide or intrathecal cytarabine (for neurotoxicity) in cases refractory to corticosteroids and IL6 antagonism [132]. Other strategies to overcome systemic cytokine toxicities of CAR T cells include engineering a suicide receptor (e.g., CD20 or truncated EGFR) on the CAR T cell, which can then be eliminated by antibody-dependent cellular cytotoxicity (ADCC) or complement-dependent cytotoxicity (CDC)-inducing monoclonal antibodies (e.g., rituximab or cetuximab), as well as engineering CAR T cells that secrete factors to neutralize the pro-inflammatory cytokines (e.g., anti-GM-CSF monoclonal antibody, IL1 receptor antagonists) or knock out cytokine genes [132].

5.3. Beyond CAR T Cells (CAR-NK and CAR-Macrophages)

Natural killer (NK) cells are the main anti-tumor effector cells in innate immunity and are also key mediators of ADCC [151]. More recently, adoptive transfer of NK cells has been implemented in the treatment of certain types of cancer including acute myeloid leukemia, ovarian, and breast cancer [151]. In post-ASCT MM patients, a clinical trial studying the use of ex vivo activated and expanded autologous NK cells as consolidation therapy showed NK-cell persistence in the circulation and increased granzyme B levels within the BM up to 4 weeks post-infusion [152]. The study also reported reduction in M-component and/or deepening of minimal residual disease post NK infusion [152]. Bolstered by the success of CAR T-cell therapy, research on the engineering of CAR-NK cells against MM is currently well underway; and preclinical data on CAR-NK against NKG2D ligands, CD38, and BCMA demonstrate potent and specific anti-MM cytotoxicity [153,154,155]. Compared with CAR T cells, CAR-NK cells have a number of unique advantages, including (1) minimal risk of CRS and neurotoxicity in the autologous setting and graft versus host disease in the allogeneic setting, (2) potential ease of “off-the-shelf” manufacturing owing to reduced risk of alloreactivity, and (3) the ability to natively kill tumor cells through CAR-independent mechanisms such as CD16-mediated ADCC, natural cytotoxicity receptor-mediated and/or NKG2D-mediated ligand binding [156].
Macrophages have historically been highly resistant to genetic engineering with standard lentiviral, retroviral, and adenoviral vectors, which have limited our ability to exploit them as antitumor therapeutics [157]. The group at the University of Pennsylvania recently found that chimeric adenoviral vector Ad5f35 was able to transduce primary human monocytes and macrophages with high efficiency and reproducibility. Utilizing this system, they were able to engineer CAR macrophages (CAR-Ms) [157]. CAR-Ms displayed antigen-specific phagocytosis and tumor eradication both in vitro and in two solid tumor xenograft mouse models. Notably, the CAR engineering process also polarized the macrophages towards a sustained pro-inflammatory (M1) phenotype [158]. Functional characterization showed that CAR-Ms expressed pro-inflammatory cytokine and chemokine, upregulated antigen presentation machinery, and converted bystander M2 macrophages to M1, as well as boosted anti-tumor T-cell activity [158].

5.4. Bispecific T-Cell Engagers (BiTEs)

Bispecific antibodies (BsAbs) are antibodies with two binding sites that recognize two different antigens or two different epitopes on the same antigen [159]. Three categories of BsAbs exist based on their targets: antibodies targeting (1) two different tumor antigens, (2) one tumor antigen and one immune-related molecule, and (3) two immune-related molecules [160]. Bispecific T cell-recruiting antibodies, which belong to the second category, have recently garnered a lot of interest for their ability to target tumor-associated antigens and CD3 to redirect autologous T cells against cancer cells [160]. Bispecific T-cell engagers (BiTEs) are the most well-established format of variable fragment (Fv)-based bispecific T cell-recruiting antibodies and they consist of two single-chain variable fragments (scFvs) connected by a short peptide linker. Other Fv-based formats include dual-affinity retargeting antibodies (DARTs), tandem diabody (TandAb), and single-chain diabody [160]. BiTEs require the presence of target tumor cells to induce activation and proliferation of T cells [160]. The activated T cells secrete cytolytic granzymes, which lead to tumor-cell lysis [160]. Notably, BiTEs are able to activate memory T cells without costimulatory signals such as CD28 and IL2 and can even overcome T-cell exhaustion [160]. Unlike CAR T cells, BiTEs are available off-the-shelf and do not require a prerequisite number of donor leukocytes/lymphocytes, or the expensive, time-consuming, and error-prone CAR T-cell manufacturing process [161]. Additionally, BiTEs are, in and of themselves, not living products and have relatively short half-lives so treatment can be stopped at any time to reverse immune activation and immune-related adverse events [161].
The predominant target for MM BiTE studies is BCMA, with a few studies looking at CD19, CD38, GPRC5D, and FcRH5 (Table 2). Preliminary results from eight BCMA BiTE phase 1 or 1/2 trials in heavily pretreated RRMM are very promising, boasting response rates ranging from 52–83% with minimal grade ≥3 CRS or neurotoxicity (Table 2) [162,163]. Durability of BiTEs in MM is still under investigation but preclinical studies show rapid relapse after treatment discontinuation in de novo VK*MYC mice (model of NDMM) and transient responses with relapse occurring within 3 weeks of treatment in the more aggressive transplantable VK12598 syngeneic VK*MYC model [164]. Relapse was mainly seen in mice with high initial tumor burden, and associated with loss of T-cell functionality, suggesting that high levels of tumor antigen may have the detrimental effect of overactivating T cells and may not be beneficial in vivo [164]. Notably, cyclophosphamide preconditioning was able to induce long-lasting remission in both models of MM, even after tumor rechallenge [164]. This was due to cyclophosphamide’s ability to preferentially kill Tregs and the cytoreductive effect, which tempered the activation of T cells and prevented BiTE-induced T-cell exhaustion [164]. Another method to counteract T-cell exhaustion resulting from persistent antigen stimulation or tonic receptor signaling would be to incorporate treatment-free intervals to functionally reinvigorate T cells [165].

5.5. Beyond BiTEs (Bispecific Killer Cell Engagers, Trispecific Antibodies, and BsAbs Armed T-Cell Therapy)

More recently, bispecific killer cell engagers (BiKEs) have been developed to harness the cytotoxic ability of NK cells. Instead of binding to CD3 on T cells, BiKEs recognize CD16, NKp30, or NKG2D on NK cells [166]. A number of preclinical BiKEs (e.g., BCMA × CD16A, BCMA × MICA, BCMA × NKp30, CS1-NKG2D) have demonstrated promising MM-specific cytotoxicity [167,168,169,170]. Trispecific antibodies are also currently in preclinical investigation which, in addition to a T-cell binding domain and distinct myeloma antigen binding domain, includes a third domain that binds another distinct myeloma antigen or adds either T-cell costimulatory proteins to decrease T-cell anergy or cytokines to promote effector cell activation (e.g., IL-15 containing TriKEs) [170]. An example of trispecific killer engagers (TriKEs) being studied in MM is the dual antigen targeting BCMA × CD200 × CD16A antibody called “aTriFlex” [171].
Another novel adoptive T-cell transfer-based immunotherapy that combines the advantages of CAR T cells and BiTEs is BsAbs armed T-cell therapy (BAT). After leukapheresis, leukocytes are coated with BsAbs ex vivo prior to reinfusion, which has shown favorable anti-tumor effects and allows for more precise control of potency compared with CAR T-cell therapy as the amount of BsAbs used to arm the T cells can be controlled, as can the cell dose per infusion and number of infusions [172].

6. Monoclonal Antibodies (MAbs)

6.1. CD38 MAbs

Daratumumab is a first-in-class CD38 receptor targeting IgG1k mAb. CD38 is overexpressed on MM cells but is also present at lower levels on normal plasma cells, and myeloid and lymphoid cells (including NK cells), as well as red blood cells and platelets [173,174]. By binding to CD38, daratumumab promotes MM-cell apoptosis via antibody-dependent cellular cytotoxicity (ADCC), complement-dependent cytotoxicity (CDC), inhibition of mitochondrial transfer, Fc receptor-mediated cross-linking, and antibody-dependent cellular phagocytosis [175,176]. Notably, IMiDs such as lenalidomide and pomalidomide are able to potentiate NK cell-mediated ADCC by increasing the expression of NK-cell activating ligands MICA and PVR/CD155 on MM cells, which facilitates tumor recognition and killing by NK cells [177]. Because CD38 is not exclusively expressed MM cells, off-target effects include NK depletion via cell fratricide as well as immunoparesis (defined as the reduction in levels of ≥1 immunoglobulins not associated with the patient’s specific myeloma variant) resulting from depletion of the antibody-producing plasma/B-cell population [178,179]. This is especially important given the COVID-19 pandemic we are currently in, and studies showing that MM patients mount a poor humoral response following vaccination, especially during treatment with anti-CD38 therapy [180]. One favorable on-target/off-tumor effect of CD38 mAbs is their ability to deplete immunosuppressive cells such as Tregs and Bregs [42,43].
Daratumumab was the first monoclonal antibody approved by the FDA for treatment of MM (Table 3). This occurred on November 16, 2015 following results from the SIRIUS trial, and specifically approved its use for patients with multiple myeloma who have received at least three prior lines of therapy, including a proteasome inhibitor (PI) and an immunomodulatory agent, or those patients who are double refractory to a PI and immunomodulatory agent. In the SIRIUS trial, daratumumab monotherapy for this patient population provided a 3.7-month median progression free survival (PFS) and overall response rate (ORR) of 29.2%. The following year, in November 2016, based on the results of the POLLUX and CASTOR trials, daratumumab in combination with lenalidomide and dexamethasone (Dara-Rd) or daratumumab in combination with bortezomib and dexamethasone (Dara-Vd), respectively, were approved by the FDA for treatment of patients with MM who have received at least one prior therapy [181,182,183,184]. The most recent updates of the POLLUX and CASTOR studies showed median PFS of 44.5 and 16.7 months, respectively, when compared to Rd or Vd alone, at 17.5 months and 7.1 months, respectively [183,184]. By May 2018, based on the ALCYONE study, the FDA-approved daratumumab in combination with bortezomib, melphalan, and prednisone (Dara-VMP) for the treatment of newly diagnosed multiple myeloma (NDMM) in patients who were transplant ineligible [185]. Later, in September, 2019, the FDA also approved daratumumab in combination with bortezomib, thalidomide, and dexamethasone (Dara-VTd) for treatment of NDMM in transplant-eligible patients based on results from the CASSIOPEIA study [186]. Other pertinent trials include the MAIA trial that led to the 2019 FDA approval of Dara-Rd for upfront treatment of NDMM patients who are transplant ineligible [187]. The CANDOR and EQUULEUS studies helped lead to FDA approval of carfilzomib and daratumumab with dexamethasone for RRMM [188,189]. More recently, the APOLLO study examined daratumumab in combination with pomalidomide and carfilzomib for RRMM, with its results leading to FDA approval of this regimen in July 2021 [190].
Similar to daratumumab, isatuximab targets the CD38 receptor, but binds to a different CD38 epitope (Table 4). Mechanistically, the main way isatuximab induces MM apoptosis is through ADCC [191]. Unlike daratumumab, isatuximab had minimal CDC activity [191] but is able to directly induce MM apoptosis in the absence of cross-linking antibodies and independently of effector cells, even in p53 mutant MM [192]. In March 2020, the FDA-approved isatuximab in combination with pomalidomide and dexamethasone (IPd), based on results from the ICARIA-MM study, for the treatment of adults with RRMM who have received at least two prior therapies including lenalidomide and a proteasome inhibitor [193]. A year later, in March, 2021, the FDA also approved isatuximab in combination with carfilzomib and dexamethasone (IKd) for treatment of adults with RRMM who have received one to three prior lines of therapy based on results from the IKEMA study [194].

6.2. SLAMF7 MAbs

Elotuzumab is a humanized IgG kappa monoclonal antibody that targets the signaling lymphocyte activation molecule family member 7 (SLAMF7) to promote MM killing, predominantly through NK cell-mediated ADCC, as well as macrophage-mediated ADCP [195,196,197,198]. SLAMF7 (also known as CS1, CRACC, or CD319) is highly expressed in myeloma cells but is either less strongly or not expressed by normal hematopoietic stem cells [199]. SLAMF7 is also expressed on NK cells and elotuzumab is able to bind NK cells through and activate CD16/Fc receptor-independent costimulatory signaling to enhance NK cytotoxicity via the upregulation of NKG2D, ICAM-1, and activated LFA-1 [197]. Notably, although elotuzumab binds SLAMF7 on NK cells, preclinical in vitro studies as well as patient data from clinical trials indicate that, unlike daratumumab, elotuzumab does not induce significant NK cell fratricide [200]. SLAMF7 was also highly expressed on exhausted CD8+ T cells and CD8+CD28CD57+ Tregs in patients with MM [201]. Consistent with this, gene expression profiling of SLAMF7-expressing CD8+ T cells revealed higher expression of exhaustion markers including LAG3, TNFRSF1B, CD244 (2B4), and TIM-3 compared with their SLAMF7-negative counterparts [201]. Elotuzumab was able to specifically eliminate the SLAMF7-expressing CD8+ T cells (including CD8+CD28CD57+ Tregs) through ADCP but not ADCC [201]. Soluble SLAMF7 (sSLAMF7) has been found to be overexpressed in the sera of some patients with MM but not healthy donors [195]. sSLAMF7 has been implicated in MM proliferation via homophilic interaction with surface SLAMF7 and downstream activation of SHP-2 and ERK signaling [202]. Lenalidomide, through IKZF1 degradation, decreases expression of SLAMF7 and abrogates the growth-promoting effect of sSLAMF7 [202]. Notably, elotuzumab was also able to bind and neutralize sSLAMF7 to inhibit sSLAMF7-induced MM growth [202].
FDA approval for elotuzumab was first granted in November 2015 in combination with lenalidomide and dexamethasone (ERd) for treatment of patients with RRMM and who have received one to three prior medications (Table 5). These recommendations were based on results from the ELOQUENT-2 trial, which compared ERd versus Rd alone [203]. Both median PFS in months and ORR were improved in the ERd compared with the Rd cohort at 19.4 months vs. 14.9 months and 79% vs. 66%, respectively [203]. In November 2018, based on the ELOQUENT-3 study, the FDA then approved elotuzumab in combination with pomalidomide and dexamethasone (EPd) for the treatment of patients with RRMM who had received at least two prior therapies including lenalidomide and a proteasome inhibitor [204]. ELOQUENT-3 compared patients on EPd versus pomalidomide and dexamethasone (Pd) alone and found almost a doubling of both the median PFS and ORR [204].

6.3. Antibody Drug Conjugates (ADCs)

Antibody drug conjugates (ADCs) are a class of highly targeted biopharmaceutical drugs consisting of a potent cytotoxic compound chemically linked to a monoclonal antibody. ADC binding to a specific tumor-associated antigen results in internalization of the cytotoxic payload and cell death. ADCs, therefore, do not solely rely on the recruitment of effector cells or activation of complement cascade to kill MM cells [205].
Belantamab is the first-in-class ADC consisting of an anti–B-cell maturation antigen (BCMA)-directed antibody conjugated to monomethyl auristatin F (MMAF), a microtubule inhibitor [51]. Belantamab eliminates MM cells by (1) triggering cell-cycle arrest through MMAF inhibition of the microtubule network, (2) inhibiting BAFF/APRIL binding to BCMA and downstream NF-κB activation, and (3) enhancing ADCC [51]. In August 2020, the FDA-approved belantamab for treatment of adult patients with RRMM who had previously received at least four therapies, including an anti-CD38 monoclonal antibody, a proteasome inhibitor, and an immunomodulatory agent (Table 6) [206]. Approval was granted based on results from the DREAMM-2 study, a phase II, open-label, two-arm multicenter trial, which found an ORR of 31% (median PFS 5.7 months) for patients who received the recommended dose of 2.5 mg/kg of belantamab [206]. Examples of ADCs currently under clinical investigation include lorvotuzumab mertansine (anti-CD56 conjugated with maytansinoid) [207], milatuzumab doxorubicin (anti-CD74 conjugated to doxorubicin [208], and indatuximab ravtansine (anti-CD138 conjugated to maytansinoid) [209].

6.4. MAbs against Other Targets

Other targets for which mAbs are currently being developed are B-cell activating factor (BAFF; NCT01556438) [210], CD74 (NCT00421525) [211], and IL6 [212], as well as the immune checkpoint proteins programmed cell death 1 (PD1; NCT01592370) [213,214] and its ligand (PDL1; NCT02579863, NCT02431208) [215,216], cytotoxic T-lymphocyte-associated protein 4 (CTLA-4; NCT01592370) [217], lymphocyte-activation gene 3 (LAG3; NCT04150965), and T-cell immunoreceptor with Ig and ITIM domains (TIGIT; NCT04150965).

7. Conclusions and Future Perspectives

The therapeutic landscape in MM has evolved significantly since Melphalan was first used in 1958. Although the introduction of novel therapies such as proteasome inhibitors, IMiDs, have led to great improvement in patient outcomes, these agents are eventually cleared from the body over time, making it difficult to achieve durable responses without continual administration. In fact, most patients still relapse even when these therapies are used in maintenance regimens. Whole-genome studies of paired samples from non-high-risk SMM patients that progressed to MM revealed a subset of patients in which the SMM clone was genomically indistinguishable from the clone at time of progression to MM [10]. A key determinant of progression in MM is therefore a permissive BM microenvironment. It is becoming increasingly apparent that immunotherapy may be the key to producing lasting remission and a functional cure in MM given that, just like MM, the immune system is “living” and has the ability to persist and adapt continuously and dynamically. Multiple strategies to reprogram the immune system against MM have been developed and many of them have unprecedented clinical efficacy even in the heavily pretreated relapsed refractory setting. However, the current state of immunotherapy in MM is still plagued by short-lived responses and a large reason is that MM creates an immunosuppressive BM tumor microenvironment, and studies have shown that the MM microenvironment is highly enriched for suppressive immune cells such as MDSCs, Tregs, pDCs, Bregs, N2 neutrophils, M2 macrophages, which leads to effector cell dysfunction and lack of persistence. A more in-depth understanding of the interactions between the MM and BM microenvironment is therefore necessary to identify and overcome immune escape mechanisms and develop novel therapies, as well as effective combinations of pre-existing therapies that will edge us closer to a cure for MM.

Author Contributions

Conceptualization: M.H., S.Z. and G.B.; writing—original draft preparation: M.H., A.X., D.Y. and S.Z.; writing—review and editing: M.H., S.Z. and G.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. van de Donk, N.W.C.J.; Pawlyn, C.; Yong, K.L. Multiple myeloma. Lancet 2021, 397, 410–427. [Google Scholar] [CrossRef]
  2. Landgren, O.; Kyle, R.A.; Pfeiffer, R.M.; Katzmann, J.A.; Caporaso, N.E.; Hayes, R.; Dispenzieri, A.; Kumar, S.; Clark, R.J.; Baris, D.; et al. Monoclonal gammopathy of undetermined significance (MGUS) consistently precedes multiple myeloma: A prospective study. Blood 2009, 113, 5412–5417. [Google Scholar] [CrossRef] [PubMed]
  3. Weiss, B.M.; Abadie, J.; Verma, P.; Howard, R.S.; Kuehl, W.M. A monoclonal gammopathy precedes multiple myeloma in most patients. Blood 2009, 113, 5418–5422. [Google Scholar] [CrossRef]
  4. Braunlin, M.; Belani, R.; Buchanan, J.; Wheeling, T.; Kim, C. Trends in the multiple myeloma treatment landscape and survival: A U.S. analysis using 2011–2019 oncology clinic electronic health record data. Leuk. Lymphoma 2020, 62, 377–386. [Google Scholar] [CrossRef] [PubMed]
  5. Greil, C.; Engelhardt, M.; Ihorst, G.; Schoeller, K.; Bertz, H.; Marks, R.; Zeiser, R.; Duyster, J.; Einsele, H.; Finke, J.; et al. Allogeneic transplantation of multiple myeloma patients may allow long-term survival in carefully selected patients with acceptable toxicity and preserved quality of life. Haematologica 2018, 104, 370–379. [Google Scholar] [CrossRef]
  6. Lightman, S.M.; Utley, A.; Lee, K.P. Survival of Long-Lived Plasma Cells (LLPC): Piecing Together the Puzzle. Front. Immunol. 2019, 10, 965. [Google Scholar] [CrossRef]
  7. 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. [Google Scholar] [CrossRef]
  8. Ho, M.; Goh, C.Y.; Patel, A.; Staunton, S.; O’Connor, R.; Godeau, M.; Bianchi, G. Role of the Bone Marrow Milieu in Multiple Myeloma Progression and Therapeutic Resistance. Clin. Lymphoma Myeloma Leuk. 2020, 20, e752–e768. [Google Scholar] [CrossRef]
  9. Dhodapkar, M.V. MGUS to myeloma: A mysterious gammopathy of underexplored significance. Blood 2016, 128, 2599–2606. [Google Scholar] [CrossRef]
  10. Bolli, N.; Maura, F.; Minvielle, S.; Gloznik, D.; Szalat, R.; Fullam, A.; Martincorena, I.; Dawson, K.J.; Samur, M.K.; Zamora, J.; et al. Genomic patterns of progression in smoldering multiple myeloma. Nat. Commun. 2018, 9, 1–10. [Google Scholar] [CrossRef]
  11. Barwick, B.; Gupta, V.A.; Vertino, P.M.; Boise, L.H. Cell of Origin and Genetic Alterations in the Pathogenesis of Multiple Myeloma. Front. Immunol. 2019, 10, 1121. [Google Scholar] [CrossRef] [PubMed]
  12. Armitage, R.J.; Fanslow, W.C.; Strockbine, L.; Sato, T.A.; Clifford, K.N.; Macduff, B.M.; Anderson, D.M.; Gimpel, S.D.; Davis-Smith, T.; Maliszewski, C.R.; et al. Molecular and biological characterization of a murine ligand for CD40. Nature 1992, 357, 80–82. [Google Scholar] [CrossRef] [PubMed]
  13. Noelle, R.J.; Roy, M.; Shepherd, D.M.; Stamenkovic, I.; Ledbetter, J.A.; Aruffo, A. A 39-kDa protein on activated helper T cells binds CD40 and transduces the signal for cognate activation of B cells. Proc. Natl. Acad. Sci. USA 1992, 89, 6550–6554. [Google Scholar] [CrossRef] [PubMed]
  14. Mosmann, T.R.; Cherwinski, H.; Bond, M.W.; Giedlin, M.A.; Coffman, R.L. Two types of murine helper T cell clone. I. Definition according to profiles of lymphokine activities and secreted proteins. J. Immunol. 1986, 136, 2348–2357. [Google Scholar] [PubMed]
  15. Snapper, C.M.; Paul, W.E. Interferon-γ and B Cell Stimulatory Factor-1 Reciprocally Regulate Ig Isotype Production. Science 1987, 236, 944–947. [Google Scholar] [CrossRef]
  16. Muraguchi, A.; Hirano, T.; Tang, B.; Matsuda, T.; Horii, Y.; Nakajima, K.; Kishimoto, T. The essential role of B cell stimulatory factor 2 (BSF-2/IL-6) for the terminal differentiation of B cells. J. Exp. Med. 1988, 167, 332–344. [Google Scholar] [CrossRef]
  17. Maeda, K.; Mehta, H.; Drevets, D.A.; Coggeshall, K.M. IL-6 increases B-cell IgG production in a feed-forward proinflammatory mechanism to skew hematopoiesis and elevate myeloid production. Blood 2010, 115, 4699–4706. [Google Scholar] [CrossRef]
  18. MacLennan, I.C.M. Germinal Centers. Annu. Rev. Immunol. 1994, 12, 117–139. [Google Scholar] [CrossRef]
  19. Victora, G.D.; Nussenzweig, M.C. Germinal Centers. Annu. Rev. Immunol. 2012, 30, 429–457. [Google Scholar] [CrossRef]
  20. Jacob, J.; Kelsoe, G.; Rajewsky, K.; Weiss, U. Intraclonal generation of antibody mutants in germinal centres. Nature 1991, 354, 389–392. [Google Scholar] [CrossRef]
  21. Menu, E.; Asosingh, K.; Indraccolo, S.; De Raeve, H.; Van Riet, I.; Van Valckenborgh, E.; Van De Broek, I.; Fujii, N.; Tamamura, H.; Van Camp, B.; et al. The involvement of stromal derived factor 1alpha in homing and progression of multiple myeloma in the 5TMM model. Haematologica 2006, 91, 605–612. [Google Scholar] [PubMed]
  22. Ho, M.; Patel, A.; Goh, C.Y.; Moscvin, M.; Zhang, L.; Bianchi, G. Changing paradigms in diagnosis and treatment of monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). Leukemia 2020, 34, 3111–3125. [Google Scholar] [CrossRef] [PubMed]
  23. Hanahan, D.; Weinberg, R.A. Hallmarks of cancer: The next generation. Cell 2011, 144, 646–674. [Google Scholar] [CrossRef] [PubMed]
  24. O’Donnell, J.S.; Teng, M.W.L.; Smyth, M.J. Cancer immunoediting and resistance to T cell-based immunotherapy. Nat. Rev. Clin. Oncol. 2019, 16, 151–167. [Google Scholar] [CrossRef] [PubMed]
  25. Knight, A.; Rihova, L.; Kralova, R.; Penka, M.; Adam, Z.; Pour, L.; Piskacek, M.; Hajek, R. Plasmacytoid Dendritic Cells in Patients with MGUS and Multiple Myeloma. J. Clin. Med. 2021, 10, 3717. [Google Scholar] [CrossRef] [PubMed]
  26. Corthay, A. How do Regulatory T Cells Work? Scand. J. Immunol. 2009, 70, 326–336. [Google Scholar] [CrossRef]
  27. Shevyrev, D.; Tereshchenko, V. Treg Heterogeneity, Function, and Homeostasis. Front. Immunol. 2020, 10, 3100. [Google Scholar] [CrossRef]
  28. Vignali, D.A.A.; Collison, L.W.; Workman, C.J. How regulatory T cells work. Nat. Rev. Immunol. 2008, 8, 523–532. [Google Scholar] [CrossRef]
  29. Feyler, S.; von Lilienfeld-Toal, M.; Jarmin, S.; Marles, L.; Rawstron, A.; Ashcroft, A.J.; Owen, R.G.; Selby, P.J.; Cook, G. CD4+CD25+FoxP3+regulatory T cells are increased whilst CD3+CD4CD8αβTCR+Double Negative T cells are decreased in the peripheral blood of patients with multiple myeloma which correlates with disease burden. Br. J. Haematol. 2009, 144, 686–695. [Google Scholar] [CrossRef]
  30. 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]
  31. Zheng, S.G.; Wang, J.; Wang, P.; Gray, J.D.; Horwitz, D.A. IL-2 Is Essential for TGF-β to Convert Naive CD4+CD25 Cells to CD25+Foxp3+ Regulatory T Cells and for Expansion of These Cells. J. Immunol. 2007, 178, 2018–2027. [Google Scholar] [CrossRef] [PubMed]
  32. 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]
  33. Scott, G.B.; Carter, C.; Parrish, C.; Wood, P.M.; Cook, G. Downregulation of myeloma-induced ICOS-L and regulatory T cell generation by lenalidomide and dexamethasone therapy. Cell. Immunol. 2015, 297, 1–9. [Google Scholar] [CrossRef]
  34. Minnema, M.C.; Van Der Veer, M.S.; Aarts, T.; Emmelot, M.; Mutis, T.; Lokhorst, H.M. Lenalidomide alone or in combination with dexamethasone is highly effective in patients with relapsed multiple myeloma following allogeneic stem cell transplantation and increases the frequency of CD4+Foxp3+ T cells. Leukemia 2008, 23, 605–607. [Google Scholar] [CrossRef] [PubMed]
  35. Lee, B.-N.; Gao, H.; Cohen, E.N.; Badoux, X.; Wierda, W.G.; Estrov, Z.; Faderl, S.H.; Keating, M.J.; Ferrajoli, A.; Reuben, J.M.; et al. Treatment with lenalidomide modulates T-cell immunophenotype and cytokine production in patients with chronic lymphocytic leukemia. Cancer 2011, 117, 3999–4008. [Google Scholar] [CrossRef] [PubMed]
  36. Gupta, R.; Ganeshan, P.; Hakim, M.; Verma, R.; Sharma, A.; Kumar, L. Significantly reduced regulatory T cell population in patients with untreated multiple myeloma. Leuk. Res. 2011, 35, 874–878. [Google Scholar] [CrossRef]
  37. Raja, K.R.M.; Kovářová, L.; Hajek, R. Induction by lenalidomide and dexamethasone combination increases regulatory cells of patients with previously untreated multiple myeloma. Leuk. Lymphoma 2012, 53, 1406–1408. [Google Scholar] [CrossRef]
  38. Quach, H.; Ritchie, D.; Stewart, A.K.; Neeson, P.; Harrison, S.; Smyth, M.J.; Prince, H.M. Mechanism of action of immunomodulatory drugs (IMiDS) in multiple myeloma. Leukemia 2009, 24, 22–32. [Google Scholar] [CrossRef]
  39. Lutsiak, M.E.C.; Semnani, R.T.; De Pascalis, R.; Kashmiri, S.V.S.; Schlom, J.; Sabzevari, H. Inhibition of CD4+25+ T regulatory cell function implicated in enhanced immune response by low-dose cyclophosphamide. Blood 2005, 105, 2862–2868. [Google Scholar] [CrossRef]
  40. Ghiringhelli, F.; Larmonier, N.; Schmitt, E.; Parcellier, A.; Cathelin, D.; Garrido, C.; Chauffert, B.; Solary, E.; Bonnotte, B.; Martin, F. CD4+CD25+ regulatory T cells suppress tumor immunity but are sensitive to cyclophosphamide which allows immunotherapy of established tumors to be curative. Eur. J. Immunol. 2004, 34, 336–344. [Google Scholar] [CrossRef]
  41. Sharabi, A.; Laronne-Bar-On, A.; Meshorer, A.; Haran-Ghera, N. Chemoimmunotherapy Reduces the Progression of Multiple Myeloma in a Mouse Model. Cancer Prev. Res. 2010, 3, 1265–1276. [Google Scholar] [CrossRef] [PubMed]
  42. Krejcik, J.; Casneuf, T.; Nijhof, I.S.; Verbist, B.; Bald, J.; Plesner, T.; Syed, K.; Liu, K.; Van De Donk, N.W.C.J.; Weiss, B.M.; et al. Daratumumab depletes CD38+ immune regulatory cells, promotes T-cell expansion, and skews T-cell repertoire in multiple myeloma. Blood 2016, 128, 384–394. [Google Scholar] [CrossRef]
  43. Feng, X.; Zhang, L.; Acharya, C.; An, G.; Wen, K.; Qiu, L.; Munshi, N.C.; Tai, Y.-T.; Anderson, K.C. Targeting CD38 Suppresses Induction and Function of T Regulatory Cells to Mitigate Immunosuppression in Multiple Myeloma. Clin. Cancer Res. 2017, 23, 4290–4300. [Google Scholar] [CrossRef]
  44. Kitadate, A.; Kobayashi, H.; Abe, Y.; Narita, K.; Miura, D.; Takeuchi, M.; Matsue, K. Pre-treatment CD38-positive regulatory T cells affect the durable response to daratumumab in relapsed/refractory multiple myeloma patients. Haematologica 2019, 105, e37–e40. [Google Scholar] [CrossRef] [PubMed]
  45. Munn, D.H.; Sharma, M.D.; Baban, B.; Harding, H.P.; Zhang, Y.; Ron, D.; Mellor, A.L. GCN2 Kinase in T Cells Mediates Proliferative Arrest and Anergy Induction in Response to Indoleamine 2,3-Dioxygenase. Immunity 2005, 22, 633–642. [Google Scholar] [CrossRef]
  46. Bonanno, G.; Mariotti, A.; Procoli, A.; Folgiero, V.; Natale, D.; De Rosa, L.; Majolino, I.; Novarese, L.; Rocci, A.; Gambella, M.; et al. Indoleamine 2,3-dioxygenase 1 (IDO1) activity correlates with immune system abnormalities in multiple myeloma. J. Transl. Med. 2012, 10, 247. [Google Scholar] [CrossRef] [PubMed]
  47. Francisco, L.M.; Salinas, V.H.; Brown, K.E.; Vanguri, V.K.; Freeman, G.J.; Kuchroo, V.K.; Sharpe, A.H. PD-L1 regulates the development, maintenance, and function of induced regulatory T cells. J. Exp. Med. 2009, 206, 3015–3029. [Google Scholar] [CrossRef]
  48. Amarnath, S.; Mangus, C.W.; Wang, J.C.M.; Wei, F.; He, A.; Kapoor, V.; Foley, J.E.; Massey, P.R.; Felizardo, T.C.; Riley, J.L.; et al. The PDL1-PD1 Axis Converts Human T H 1 Cells into Regulatory T Cells. Sci. Transl. Med. 2011, 3, 111ra120. [Google Scholar] [CrossRef]
  49. Matthes, T.; Dunand-Sauthier, I.; Santiago-Raber, M.-L.; Krause, K.-H.; Donze, O.; Passweg, J.; McKee, T.; Huard, B. Production of the plasma-cell survival factor a proliferation-inducing ligand (APRIL) peaks in myeloid precursor cells from human bone marrow. Blood 2011, 118, 1838–1844. [Google Scholar] [CrossRef]
  50. Tai, Y.-T.; Lin, L.; Xing, L.; Cho, S.-F.; Yu, T.; Acharya, C.; Wen, K.; Hsieh, P.A.; Dulos, J.; Van Elsas, A.; et al. APRIL signaling via TACI mediates immunosuppression by T regulatory cells in multiple myeloma: Therapeutic implications. Leukemia 2018, 33, 426–438. [Google Scholar] [CrossRef]
  51. Tai, Y.-T.; Acharya, C.; An, G.; Moschetta, M.; Zhong, M.Y.; Feng, X.; Cea, M.; Cagnetta, A.; Wen, K.; Van Eenennaam, H.; et al. APRIL and BCMA promote human multiple myeloma growth and immunosuppression in the bone marrow microenvironment. Blood 2016, 127, 3225–3236. [Google Scholar] [CrossRef] [PubMed]
  52. 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]
  53. 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] [PubMed]
  54. Brimnes, M.K.; Vangsted, A.J.; Knudsen, L.M.; Gimsing, P.; Gang, A.O.; Johnsen, H.E.; Svane, I.M. Increased Level of both CD4+FOXP3+ Regulatory T Cells and CD14+HLA-DR−/low Myeloid-Derived Suppressor Cells and Decreased Level of Dendritic Cells in Patients with Multiple Myeloma. Scand. J. Immunol. 2010, 72, 540–547. [Google Scholar] [CrossRef]
  55. Beyer, M.; Kochanek, M.; Giese, T.; Endl, E.; Weihrauch, M.R.; Knolle, P.A.; Classen, S.; Schultze, J.L. In vivo peripheral expansion of naive CD4+CD25highFoxP3+ regulatory T cells in patients with multiple myeloma. Blood 2006, 107, 3940–3949. [Google Scholar] [CrossRef] [PubMed]
  56. 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] [PubMed]
  57. 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]
  58. D’Arena, G.; Rossi, G.; Laurenti, L.; Statuto, T.; D’Auria, F.; Valvano, L.; Simeon, V.; Giudice, A.; Innocenti, I.; De Feo, V.; et al. Circulating Regulatory T-Cells in Monoclonal Gammopathies of Uncertain Significance and Multiple Myeloma: In Search of a Role. J. Immunol. Res. 2016, 2016, 1–7. [Google Scholar] [CrossRef]
  59. Lad, D.; Huang, Q.; Hoeppli, R.; Garcia, R.; Xu, L.; Levings, M.; Song, K.; Broady, R. Evaluating the role of Tregs in the progression of multiple myeloma. Leuk. Lymphoma 2019, 60, 2134–2142. [Google Scholar] [CrossRef]
  60. Favaloro, J.; Brown, R.; Aklilu, E.; Yang, S.; Suen, H.; Hart, D.; Fromm, P.; Gibson, J.; Khoo, L.; Ho, P.J.; et al. Myeloma skews regulatory T and pro-inflammatory T helper 17 cell balance in favor of a suppressive state. Leuk. Lymphoma 2013, 55, 1090–1098. [Google Scholar] [CrossRef]
  61. Braga, W.M.T.; Da Silva, B.R.; de Carvalho, A.C.; Maekawa, Y.H.; Bortoluzzo, A.; Gil Rizzatti, E.; 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]
  62. Li, S.; Wu, J.; Zhu, S.; Liu, Y.-J.; Chen, J. Disease-Associated Plasmacytoid Dendritic Cells. Front. Immunol. 2017, 8. [Google Scholar] [CrossRef] [PubMed]
  63. Lombardi, V.C.; Khaiboullina, S.F.; Rizvanov, A.A. Plasmacytoid dendritic cells, a role in neoplastic prevention and progression. Eur. J. Clin. Investig. 2014, 45, 1–8. [Google Scholar] [CrossRef]
  64. Chauhan, D.; Singh, A.V.; Brahmandam, M.; Carrasco, R.; Bandi, M.; Hideshima, T.; Bianchi, G.; Podar, K.; Tai, Y.-T.; Mitsiades, C.; et al. Functional Interaction of Plasmacytoid Dendritic Cells with Multiple Myeloma Cells: A Therapeutic Target. Cancer Cell 2009, 16, 309–323. [Google Scholar] [CrossRef]
  65. Ray, A.; Das, D.S.; Song, Y.; Richardson, P.; Munshi, N.C.; Chauhan, D.; Anderson, K.C. Targeting PD1–PDL1 immune checkpoint in plasmacytoid dendritic cell interactions with T cells, natural killer cells and multiple myeloma cells. Leukemia 2015, 29, 1441–1444. [Google Scholar] [CrossRef] [PubMed]
  66. Stocker, N.; Gaugler, B.; Ricard, L.; De Vassoigne, F.; Marjanovic, Z.; Mohty, M.; Malard, F. Daratumumab prevents programmed death ligand-1 expression on antigen-presenting cells in de novo multiple myeloma. Cancer Med. 2020, 9, 2077–2084. [Google Scholar] [CrossRef] [PubMed]
  67. Malek, E.; de Lima, M.; Letterio, J.J.; Kim, B.-G.; Finke, J.H.; Driscoll, J.J.; Giralt, S.A. Myeloid-derived suppressor cells: The green light for myeloma immune escape. Blood Rev. 2016, 30, 341–348. [Google Scholar] [CrossRef] [PubMed]
  68. Ostrand-Rosenberg, S.; Fenselau, C. Myeloid-Derived Suppressor Cells: Immune-Suppressive Cells That Impair Antitumor Immunity and Are Sculpted by Their Environment. J. Immunol. 2018, 200, 422–431. [Google Scholar] [CrossRef]
  69. Wang, Z.; Zhang, L.; Wang, H.; Xiong, S.; Li, Y.; Tao, Q.; Xiao, W.; Qin, H.; Wang, Y.; Zhai, Z. Tumor-induced CD14+HLA-DR−/low myeloid-derived suppressor cells correlate with tumor progression and outcome of therapy in multiple myeloma patients. Cancer Immunol. Immunother. 2014, 64, 389–399. [Google Scholar] [CrossRef]
  70. Rodriguez, P.C.; Quiceno, D.G.; Zabaleta, J.; Ortiz, B.; Zea, A.H.; Piazuelo, M.B.; Delgado, A.; Correa, P.; Brayer, J.; Sotomayor, E.M.; et al. Arginase I Production in the Tumor Microenvironment by Mature Myeloid Cells Inhibits T-Cell Receptor Expression and Antigen-Specific T-Cell Responses. Cancer Res 2004, 64, 5839–5849. [Google Scholar] [CrossRef]
  71. Rodriguez, P.C.; Quiceno, D.G.; Ochoa, A.C. l-arginine availability regulates T-lymphocyte cell-cycle progression. Blood 2007, 109, 1568–1573. [Google Scholar] [CrossRef] [PubMed]
  72. Mannick, J.B.; Hausladen, A.; Liu, L.; Hess, D.T.; Zeng, M.; Miao, Q.X.; Kane, L.S.; Gow, A.J.; Stamler, J.S. Fas-Induced Caspase Denitrosylation. Science 1999, 284, 651–654. [Google Scholar] [CrossRef]
  73. Bronte, V.; Serafini, P.; De Santo, C.; Marigo, I.; Tosello, V.; Mazzoni, A.; Segal, D.M.; Staib, C.; Lowel, M.; Sutter, G.; et al. IL-4-Induced Arginase 1 Suppresses Alloreactive T Cells in Tumor-Bearing Mice. J. Immunol. 2003, 170, 270–278. [Google Scholar] [CrossRef] [PubMed]
  74. 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] [PubMed]
  75. 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] [PubMed]
  76. Kuwahara-Ota, S.; Shimura, Y.; Steinebach, C.; Isa, R.; Yamaguchi, J.; Nishiyama, D.; Fujibayashi, Y.; Takimoto-Shimomura, T.; Mizuno, Y.; Matsumura-Kimoto, Y.; et al. Lenalidomide and pomalidomide potently interfere with induction of myeloid-derived suppressor cells in multiple myeloma. Br. J. Haematol. 2020, 191, 784–795. [Google Scholar] [CrossRef]
  77. De Veirman, K.; Rao, L.; De Bruyne, E.; Menu, E.; Van Valckenborgh, E.; Van Riet, I.; Frassanito, M.A.; Di Marzo, L.; Vacca, A.; Vanderkerken, K. Cancer Associated Fibroblasts and Tumor Growth: Focus on Multiple Myeloma. Cancers 2014, 6, 1363–1381. [Google Scholar] [CrossRef]
  78. Frassanito, M.A.; Rao, L.; Moschetta, M.; Ria, R.; Di Marzo, L.; De Luisi, A.; Racanelli, V.; Catacchio, I.; Berardi, S.; Basile, A.; et al. Bone marrow fibroblasts parallel multiple myeloma progression in patients and mice: In vitro and in vivo studies. Leukemia 2013, 28, 904–916. [Google Scholar] [CrossRef]
  79. 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]
  80. Mosser, D.M.; Edwards, J.P. Exploring the full spectrum of macrophage activation. Nat. Rev. Immunol. 2008, 8, 958–969. [Google Scholar] [CrossRef]
  81. Rendra, E.; Riabov, V.; Mossel, D.M.; Sevastyanova, T.; Harmsen, M.C.; Kzhyshkowska, J. Reactive oxygen species (ROS) in macrophage activation and function in diabetes. Immunobiology 2018, 224, 242–253. [Google Scholar] [CrossRef] [PubMed]
  82. Xue, Q.; Yan, Y.; Zhang, R.; Xiong, H. Regulation of iNOS on Immune Cells and Its Role in Diseases. Int. J. Mol. Sci. 2018, 19, 3805. [Google Scholar] [CrossRef] [PubMed]
  83. Werner, S.; Grose, R. Regulation of Wound Healing by Growth Factors and Cytokines. Physiol. Rev. 2003, 83, 835–870. [Google Scholar] [CrossRef]
  84. Roberts, A.B.; Sporn, M.B.; Assoian, R.K.; Smith, J.M.; Roche, N.S.; Wakefield, L.M.; Heine, U.I.; Liotta, L.A.; Falanga, V.; Kehrl, J.H. Transforming growth factor type beta: Rapid induction of fibrosis and angiogenesis in vivo and stimulation of collagen formation in vitro. Proc. Natl. Acad. Sci. USA 1986, 83, 4167–4171. [Google Scholar] [CrossRef]
  85. Ahmad, A. Epigenetic regulation of immunosuppressive tumor-associated macrophages through dysregulated microRNAs. Semin. Cell Dev. Biol. 2021, 124, 26–33. [Google Scholar] [CrossRef] [PubMed]
  86. Salah, A.; Li, Y.; Wang, H.; Qi, N.; Wu, Y. Macrophages as a Double-Edged Weapon: The Use of Macrophages in Cancer Immunotherapy and Understanding the Cross-Talk Between Macrophages and Cancer. DNA Cell Biol. 2021, 40, 429–440. [Google Scholar] [CrossRef]
  87. Petty, A.J.; Yang, Y. Tumor-Associated Macrophages in Hematologic Malignancies: New Insights and Targeted Therapies. Cells 2019, 8, 1526. [Google Scholar] [CrossRef]
  88. Ribatti, D.; Moschetta, M.; Vacca, A. Macrophages in multiple myeloma. Immunol. Lett. 2014, 161, 241–244. [Google Scholar] [CrossRef]
  89. Papadimitriou, K.; Tsakirakis, N.; Malandrakis, P.; Vitsos, P.; Metousis, A.; Orologas-Stavrou, N.; Ntanasis-Stathopoulos, I.; Kanellias, N.; Eleutherakis-Papaiakovou, E.; Pothos, P.; et al. Deep Phenotyping Reveals Distinct Immune Signatures Correlating with Prognostication, Treatment Responses, and MRD Status in Multiple Myeloma. Cancers 2020, 12, 3245. [Google Scholar] [CrossRef]
  90. Wang, H.; Hu, W.-M.; Xia, Z.-J.; Liang, Y.; Lu, Y.; Lin, S.-X.; 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]
  91. Suyanı, E.; Sucak, G.T.; Akyürek, N.; Şahin, S.; Baysal, N.A.; Yağcı, M.; Haznedar, R. Tumor-associated macrophages as a prognostic parameter in multiple myeloma. Ann. Hematol. 2013, 92, 669–677. [Google Scholar] [CrossRef] [PubMed]
  92. Sun, J.; Muz, B.; Alhallak, K.; Park, C.; Lubben, B.; Fiala, M.; Vij, R.; Azab, A.K. P-079: IL10R inhibition reprograms tumor-associated macrophages and reverses drug resistance in Multiple Myeloma. Clin. Lymphoma Myeloma Leuk. 2021, 21, S82. [Google Scholar] [CrossRef]
  93. Kim, J.; Denu, R.A.; Dollar, B.A.; Escalante, L.E.; Kuether, J.P.; Callander, N.; Asimakopoulos, F.; Hematti, P. Macrophages and mesenchymal stromal cells support survival and proliferation of multiple myeloma cells. Br. J. Haematol. 2012, 158, 336–346. [Google Scholar] [CrossRef] [PubMed]
  94. Yan, H.; Dong, M.; Liu, X.; Shen, Q.; He, D.; Huang, X.; Zhang, E.; Lin, X.; Chen, Q.; Guo, X.; et al. Multiple myeloma cell-derived IL-32γ increases the immunosuppressive function of macrophages by promoting indoleamine 2,3-dioxygenase (IDO) expression. Cancer Lett. 2019, 446, 38–48. [Google Scholar] [CrossRef]
  95. 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] [PubMed]
  96. 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] [PubMed]
  97. Tu, M.M.; Abdel-Hafiz, H.A.; Jones, R.T.; Jean, A.; Hoff, K.J.; Duex, J.E.; Chauca-Diaz, A.; Costello, J.C.; Dancik, G.M.; Tamburini, B.A.J.; et al. Inhibition of the CCL2 receptor, CCR2, enhances tumor response to immune checkpoint therapy. Commun. Biol. 2020, 3, 1–12. [Google Scholar] [CrossRef]
  98. Nywening, T.M.; Wang-Gillam, A.; Sanford, D.E.; Belt, B.A.; Panni, R.Z.; Cusworth, B.M.; Toriola, A.T.; Nieman, R.K.; Worley, L.A.; Yano, M.; et al. Targeting tumour-associated macrophages with CCR2 inhibition in combination with FOLFIRINOX in patients with borderline resectable and locally advanced pancreatic cancer: A single-centre, open-label, dose-finding, non-randomised, phase 1b trial. Lancet Oncol. 2016, 17, 651–662. [Google Scholar] [CrossRef]
  99. Li, X.; Yao, W.; Yuan, Y.; Chen, P.; Li, B.; Li, J.; Chu, R.; Song, H.; Xie, D.; Jiang, X.; et al. Targeting of tumour-infiltrating macrophages via CCL2/CCR2 signalling as a therapeutic strategy against hepatocellular carcinoma. Gut 2015, 66, 157–167. [Google Scholar] [CrossRef]
  100. 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 2017, 32, 176–183. [Google Scholar] [CrossRef]
  101. Chen, H.; Li, M.; Sanchez, E.; Soof, C.M.; Bujarski, S.; Ng, N.; Cao, J.; Hekmati, T.; Zahab, B.; Nosrati, J.D.; et al. JAK1/2 pathway inhibition suppresses M2 polarization and overcomes resistance of myeloma to lenalidomide by reducing TRIB1, MUC1, CD44, CXCL12, and CXCR4 expression. Br. J. Haematol. 2019, 188, 283–294. [Google Scholar] [CrossRef]
  102. Shaul, M.E.; Fridlender, Z.G. Tumour-associated neutrophils in patients with cancer. Nat. Rev. Clin. Oncol. 2019, 16, 601–620. [Google Scholar] [CrossRef] [PubMed]
  103. Bronte, V.; Brandau, S.; Chen, S.-H.; Colombo, M.P.; Frey, A.B.; Greten, T.F.; Mandruzzato, S.; Murray, P.J.; Ochoa, A.; Ostrand-Rosenberg, S.; et al. Recommendations for myeloid-derived suppressor cell nomenclature and characterization standards. Nat. Commun. 2016, 7, 12150. [Google Scholar] [CrossRef]
  104. Romano, A.; Parrinello, N.L.; Simeon, V.; Puglisi, F.; La Cava, P.; Bellofiore, C.; Giallongo, C.; Camiolo, G.; D’Auria, F.; Grieco, V.; et al. High-density neutrophils in MGUS and multiple myeloma are dysfunctional and immune-suppressive due to increased STAT3 downstream signaling. Sci. Rep. 2020, 10, 1–18. [Google Scholar] [CrossRef] [PubMed]
  105. Petersson, J.; Askman, S.; Pettersson, Å.; Wichert, S.; Hellmark, T.; Johansson, C.M.; Hansson, M. Bone Marrow Neutrophils of Multiple Myeloma Patients Exhibit Myeloid-Derived Suppressor Cell Activity. J. Immunol. Res. 2021, 2021, 1–10. [Google Scholar] [CrossRef]
  106. Catalán, D.; Mansilla, M.A.; Ferrier, A.; Soto, L.; Oleinika, K.; Aguillón, J.C.; Aravena, O. Immunosuppressive Mechanisms of Regulatory B Cells. Front. Immunol. 2021, 12. [Google Scholar] [CrossRef] [PubMed]
  107. 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]
  108. 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]
  109. Papoutselis, M.; Spanoudakis, E. Navigating the Role of CD1d/Invariant Natural Killer T-cell/Glycolipid Immune Axis in Multiple Myeloma Evolution: Therapeutic Implications. Clin. Lymphoma Myeloma Leuk. 2020, 20, 358–365. [Google Scholar] [CrossRef]
  110. Mozaffari, F.; Hansson, L.; Kiaii, S.; Ju, X.; Rossmann, E.D.; Rabbani, H.; Mellstedt, H.; Österborg, A. Signalling molecules and cytokine production in T cells of multiple myeloma-increased abnormalities with advancing stage. Br. J. Haematol. 2004, 124, 315–324. [Google Scholar] [CrossRef]
  111. An, G.; Acharya, C.; Feng, X.; Wen, K.; Zhong, M.; Zhang, L.; Munshi, N.C.; Qiu, L.; Tai, Y.-T.; Anderson, K.C. Osteoclasts promote immune suppressive microenvironment in multiple myeloma: Therapeutic implication. Blood 2016, 128, 1590–1603. [Google Scholar] [CrossRef] [PubMed]
  112. 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, 1–12. [Google Scholar] [CrossRef] [PubMed]
  113. Liu, J.; Hamrouni, A.; Wolowiec, D.; Coiteux, V.; Kuliczkowski, K.; Hetuin, D.; Saudemont, A.; Quesnel, B. Plasma cells from multiple myeloma patients express B7-H1 (PD-L1) and increase expression after stimulation with IFN-γ and TLR ligands via a MyD88-, TRAF6-, and MEK-dependent pathway. Blood 2007, 110, 296–304. [Google Scholar] [CrossRef] [PubMed]
  114. Atanackovic, D.; Luetkens, T.; Kröger, N. Coinhibitory molecule PD-1 as a potential target for the immunotherapy of multiple myeloma. Leukemia 2013, 28, 993–1000. [Google Scholar] [CrossRef]
  115. Tamura, H.; Ishibashi, M.; Yamashita, T.; Tanosaki, S.; Okuyama, N.; Kondo, A.; Hyodo, H.; Shinya, E.; Takahashi, H.K.; Dong, H.; et al. Marrow stromal cells induce B7-H1 expression on myeloma cells, generating aggressive characteristics in multiple myeloma. Leukemia 2012, 27, 464–472. [Google Scholar] [CrossRef]
  116. Tan, J.; Chen, S.; Huang, J.; Chen, Y.; Yang, L.; Wang, C.; Zhong, J.; Lu, Y.; Wang, L.; Zhu, K.; et al. Increased exhausted CD8+T cells with programmed death-1, T-cell immunoglobulin and mucin-domain-containing-3 phenotype in patients with multiple myeloma. Asia-Pac. J. Clin. Oncol. 2018, 14, e266–e274. [Google Scholar] [CrossRef]
  117. Jing, W.; Gershan, J.A.; Weber, J.; Tlomak, D.; McOlash, L.; Sabatos-Peyton, C.; Johnson, B.D. Combined immune checkpoint protein blockade and low dose whole body irradiation as immunotherapy for myeloma. J. Immunother. Cancer 2015, 3, 2. [Google Scholar] [CrossRef]
  118. Bae, J.; Accardi, F.; Hideshima, T.; Tai, Y.-T.; Prabhala, R.; Shambley, A.; Wen, K.; Rowell, S.; Richardson, P.G.; Munshi, N.C.; et al. Targeting LAG3/GAL-3 to overcome immunosuppression and enhance anti-tumor immune responses in multiple myeloma. Leukemia 2021, 36, 138–154. [Google Scholar] [CrossRef]
  119. Tremblay-Lemay, R.; Rastgoo, N.; Chang, H. Modulating PD-L1 expression in multiple myeloma: An alternative strategy to target the PD-1/PD-L1 pathway. J. Hematol. Oncol. 2018, 11, 46. [Google Scholar] [CrossRef]
  120. Jelinek, T.; Paiva, B.; Hajek, R. Update on PD-1/PD-L1 Inhibitors in Multiple Myeloma. Front. Immunol. 2018, 9, 2431. [Google Scholar] [CrossRef]
  121. Tan, S.; Li, D.; Zhu, X. Cancer immunotherapy: Pros, cons and beyond. Biomed. Pharmacother. 2020, 124, 109821. [Google Scholar] [CrossRef] [PubMed]
  122. Abramson, J.S.; Palomba, M.L.; Gordon, L.I.; Lunning, M.A.; Wang, M.; Arnason, J.; Mehta, A.; Purev, E.; Maloney, D.G.; Andreadis, C.; et al. Lisocabtagene maraleucel for patients with relapsed or refractory large B-cell lymphomas (TRANSCEND NHL 001): A multicentre seamless design study. Lancet 2020, 396, 839–852. [Google Scholar] [CrossRef]
  123. 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]
  124. Schuster, S.J.; Bishop, M.R.; Tam, C.S.; Waller, E.K.; Borchmann, P.; McGuirk, J.P.; Jäger, U.; Jaglowski, S.; Andreadis, C.; Westin, J.R.; et al. Tisagenlecleucel in Adult Relapsed or Refractory Diffuse Large B-Cell Lymphoma. N. Engl. J. Med. 2019, 380, 45–56. [Google Scholar] [CrossRef] [PubMed]
  125. Neelapu, S.S.; Locke, F.L.; Bartlett, N.L.; Lekakis, L.J.; Miklos, D.B.; Jacobson, C.A.; Braunschweig, I.; Oluwole, O.O.; Siddiqi, T.; Lin, Y.; et al. Axicabtagene Ciloleucel CAR T-Cell Therapy in Refractory Large B-Cell Lymphoma. N. Engl. J. Med. 2017, 377, 2531–2544. [Google Scholar] [CrossRef]
  126. Wang, M.; Munoz, J.; Goy, A.; Locke, F.L.; Jacobson, C.A.; Hill, B.T.; Timmerman, J.M.; Holmes, H.; Jaglowski, S.; Flinn, I.W.; et al. KTE-X19 CAR T-Cell Therapy in Relapsed or Refractory Mantle-Cell Lymphoma. N. Engl. J. Med. 2020, 382, 1331–1342. [Google Scholar] [CrossRef] [PubMed]
  127. Carpenter, R.O.; Evbuomwan, M.O.; Pittaluga, S.; Rose, J.J.; Raffeld, M.; Yang, S.; Gress, R.E.; Hakim, F.T.; Kochenderfer, J.N. B-cell Maturation Antigen Is a Promising Target for Adoptive T-cell Therapy of Multiple Myeloma. Clin. Cancer Res. 2013, 19, 2048–2060. [Google Scholar] [CrossRef]
  128. Berdeja, J.G.; Madduri, D.; Usmani, S.Z.; Jakubowiak, A.; Agha, M.; Cohen, A.D.; Stewart, A.K.; Hari, P.; Htut, M.; Lesokhin, A.; et al. Ciltacabtagene autoleucel, a B-cell maturation antigen-directed chimeric antigen receptor T-cell therapy in patients with relapsed or refractory multiple myeloma (CARTITUDE-1): A phase 1b/2 open-label study. Lancet 2021, 398, 314–324. [Google Scholar] [CrossRef]
  129. Munshi, N.C.; Anderson, L.D., Jr.; Shah, N.; Madduri, D.; Berdeja, J.; Lonial, S.; Raje, N.; Lin, Y.; Siegel, D.; Oriol, A.; et al. Idecabtagene Vicleucel in Relapsed and Refractory Multiple Myeloma. N. Engl. J. Med. 2021, 384, 705–716. [Google Scholar] [CrossRef]
  130. Sheykhhasan, M.; Manoochehri, H.; Dama, P. Use of CAR T-cell for acute lymphoblastic leukemia (ALL) treatment: A review study. Cancer Gene Ther. 2022, 29, 1080–1096. [Google Scholar] [CrossRef]
  131. Teoh, P.J.; Chng, W.J. CAR T-cell therapy in multiple myeloma: More room for improvement. Blood Cancer J. 2021, 11, 1–18. [Google Scholar] [CrossRef] [PubMed]
  132. Rafiq, S.; Hackett, C.S.; Brentjens, R.J. Engineering strategies to overcome the current roadblocks in CAR T cell therapy. Nat. Rev. Clin. Oncol. 2019, 17, 147–167. [Google Scholar] [CrossRef] [PubMed]
  133. Shah, N.; Chari, A.; Scott, E.; Mezzi, K.; Usmani, S.Z. B-cell maturation antigen (BCMA) in multiple myeloma: Rationale for targeting and current therapeutic approaches. Leukemia 2020, 34, 985–1005. [Google Scholar] [CrossRef] [PubMed]
  134. Friedman, K.M.; Garrett, T.E.; Evans, J.W.; Horton, H.M.; Latimer, H.J.; Seidel, S.L.; Horvath, C.J.; Morgan, R.A. Effective Targeting of Multiple B-Cell Maturation Antigen–Expressing Hematological Malignances by Anti-B-Cell Maturation Antigen Chimeric Antigen Receptor T Cells. Hum. Gene Ther. 2018, 29, 585–601. [Google Scholar] [CrossRef] [PubMed]
  135. Moreaux, J.; Cremer, F.W.; Reme, T.; Raab, M.; Mahtouk, K.; Kaukel, P.; Pantesco, V.; De Vos, J.; Jourdan, E.; Jauch, A.; et al. The level of TACI gene expression in myeloma cells is associated with a signature of microenvironment dependence versus a plasmablastic signature. Blood 2005, 106, 1021–1030. [Google Scholar] [CrossRef] [PubMed]
  136. Da Vià, M.C.; Dietrich, O.; Truger, M.; Arampatzi, P.; Duell, J.; Heidemeier, A.; Zhou, X.; Danhof, S.; Kraus, S.; Chatterjee, M.; et al. Homozygous BCMA gene deletion in response to anti-BCMA CAR T cells in a patient with multiple myeloma. Nat. Med. 2021, 27, 616–619. [Google Scholar] [CrossRef]
  137. Brudno, J.N.; Maric, I.; Hartman, S.D.; Rose, J.J.; Wang, M.; Lam, N.; Stetler-Stevenson, M.; Salem, D.; Yuan, C.; Pavletic, S.; et al. T Cells Genetically Modified to Express an Anti–B-Cell Maturation Antigen Chimeric Antigen Receptor Cause Remissions of Poor-Prognosis Relapsed Multiple Myeloma. J. Clin. Oncol. 2018, 36, 2267–2280. [Google Scholar] [CrossRef]
  138. Samur, M.K.; Fulciniti, M.; Aktas-Samur, A.; Bazarbachi, A.H.; Tai, Y.-T.; Campbell, T.B.; Petrocca, F.; Hege, K.; Kaiser, S.; Anderson, K.; et al. Biallelic Loss of BCMA Triggers Resistance to Anti-BCMA CAR T Cell Therapy in Multiple Myeloma. Blood 2020, 136, 14. [Google Scholar] [CrossRef]
  139. Mikkilineni, L.; Manasanch, E.E.; Lam, B.N.; Vanasse, B.D.; Brudno, J.N.; Maric, M.I.; Rose, M.J.J.; Stetler-Stevenson, M.; Wang, H.-W.; Yuan, C.M.; et al. T Cells Expressing an Anti-B-Cell Maturation Antigen (BCMA) Chimeric Antigen Receptor with a Fully-Human Heavy-Chain-Only Antigen Recognition Domain Induce Remissions in Patients with Relapsed Multiple Myeloma. Blood 2019, 134, 3230. [Google Scholar] [CrossRef]
  140. Sotillo, E.; Barrett, D.M.; Black, K.L.; Bagashev, A.; Oldridge, D.; Wu, G.; Sussman, R.; LaNauze, C.; Ruella, M.; Gazzara, M.R.; et al. Convergence of Acquired Mutations and Alternative Splicing of CD19 Enables Resistance to CART-19 Immunotherapy. Cancer Discov. 2015, 5, 1282–1295. [Google Scholar] [CrossRef]
  141. Orlando, E.J.; Han, X.; Tribouley, C.; Wood, P.A.; Leary, R.J.; Riester, M.; Levine, J.E.; Qayed, M.; Grupp, S.A.; Boyer, M.; et al. Genetic mechanisms of target antigen loss in CAR19 therapy of acute lymphoblastic leukemia. Nat. Med. 2018, 24, 1504–1506. [Google Scholar] [CrossRef]
  142. Hamieh, M.; Dobrin, A.; Cabriolu, A.; Van Der Stegen, S.J.C.; Giavridis, T.; Mansilla-Soto, J.; Eyquem, J.; Zhao, Z.; Whitlock, B.M.; Miele, M.M.; et al. CAR T cell trogocytosis and cooperative killing regulate tumour antigen escape. Nature 2019, 568, 112–116. [Google Scholar] [CrossRef] [PubMed]
  143. Timmers, M.; Roex, G.; Wang, Y.; Campillo-Davo, D.; Van Tendeloo, V.F.I.; Chu, Y.; Berneman, Z.; Luo, F.; Van Acker, H.H.; Anguille, S. Chimeric Antigen Receptor-Modified T Cell Therapy in Multiple Myeloma: Beyond B Cell Maturation Antigen. Front. Immunol. 2019, 10, 1613. [Google Scholar] [CrossRef] [PubMed]
  144. Steiner, N.; Gunsilius, E. CAR-T cells in multiple myeloma: Current status. memo - Mag. Eur. Med Oncol. 2020, 13, 43–49. [Google Scholar] [CrossRef]
  145. Pont, M.J.; Hill, T.; Cole, G.O.; Abbott, J.J.; Kelliher, J.; Salter, A.I.; Hudecek, M.; Comstock, M.L.; Rajan, A.; Patel, B.K.R.; et al. γ-Secretase inhibition increases efficacy of BCMA-specific chimeric antigen receptor T cells in multiple myeloma. Blood 2019, 134, 1585–1597. [Google Scholar] [CrossRef]
  146. Garcia-Guerrero, E.; Rodríguez-Lobato, L.G.; Danhof, S.; Sierro-Martínez, B.; Goetz, R.; Sauer, M.; Perez-Simon, J.A.; Einsele, H.; Hudecek, M.; Prommersbe, S. ATRA Augments BCMA Expression on Myeloma Cells and Enhances Recognition By BCMA-CAR T-Cells. Blood 2020, 136, 13–14. [Google Scholar] [CrossRef]
  147. Van Der Schans, J.J.; Van De Donk, N.W.C.J.; Mutis, T. Dual Targeting to Overcome Current Challenges in Multiple Myeloma CAR T-Cell Treatment. Front. Oncol. 2020, 10, 1362. [Google Scholar] [CrossRef]
  148. Sakemura, R.; Hefazi, M.; Siegler, E.L.; Cox, M.J.; Larson, D.P.; Hansen, M.J.; Roman, C.M.; Schick, K.J.; Can, I.; Tapper, E.E.; et al. Targeting cancer-associated fibroblasts in the bone marrow prevents resistance to CART-cell therapy in multiple myeloma. Blood 2022, 139, 3708–3721. [Google Scholar] [CrossRef]
  149. Rodríguez-Lobato, L.G.; Ganzetti, M.; de Larrea, C.F.; Hudecek, M.; Einsele, H.; Danhof, S. CAR T-Cells in Multiple Myeloma: State of the Art and Future Directions. Front. Oncol. 2020, 10, 1243. [Google Scholar] [CrossRef]
  150. Dar, H.; Henderson, D.; Padalia, Z.; Porras, A.; Mu, D.; Kyungah, M.; Police, S.; Kalaitzidis, D.; Terrett, J.; Sagert, J. Preclinical Development of CTX120, an Allogeneic CAR-T Cell Targeting Bcma. Blood 2018, 132, 1921. [Google Scholar] [CrossRef]
  151. Wu, S.-Y.; Fu, T.; Jiang, Y.-Z.; Shao, Z.-M. Natural killer cells in cancer biology and therapy. Mol. Cancer 2020, 19, 1–26. [Google Scholar] [CrossRef] [PubMed]
  152. Nahi, H.; Chrobok, M.; Meinke, S.; Gran, C.; Marquardt, N.; Afram, G.; Sutlu, T.; Gilljam, M.; Stellan, B.; Wagner, A.K.; et al. Autologous NK cells as consolidation therapy following stem cell transplantation in multiple myeloma. Cell Rep. Med. 2022, 3. [Google Scholar] [CrossRef] [PubMed]
  153. Leivas, A.; Valeri, A.; Córdoba, L.; García-Ortiz, A.; Ortiz, A.; Sánchez-Vega, L.; Graña-Castro, O.; Fernández, L.; Carreño-Tarragona, G.; Pérez, M.; et al. NKG2D-CAR-transduced natural killer cells efficiently target multiple myeloma. Blood Cancer J. 2021, 11, 1–11. [Google Scholar] [CrossRef] [PubMed]
  154. Karvouni, M.; Wagner, A.K.; Baloch, A.H.; Gilljam, M.; Lundqvist, A.; Alici, E. A novel antiCD38-CAR construct increases the in vitro responsiveness of NK cells against Multiple Myeloma cells. Clin. Lymphoma Myeloma Leuk. 2019, 19, e163–e164. [Google Scholar] [CrossRef]
  155. Ng, Y.Y.; Du, Z.; Zhang, X.; Chng, W.J.; Wang, S. CXCR4 and anti-BCMA CAR co-modified natural killer cells suppress multiple myeloma progression in a xenograft mouse model. Cancer Gene Ther. 2021, 29, 475–483. [Google Scholar] [CrossRef]
  156. Xie, G.; Dong, H.; Liang, Y.; Ham, J.D.; Rizwan, R.; Chen, J. CAR-NK cells: A promising cellular immunotherapy for cancer. eBioMedicine 2020, 59, 102975. [Google Scholar] [CrossRef]
  157. Anderson, N.R.; Minutolo, N.G.; Gill, S.; Klichinsky, M. Macrophage-Based Approaches for Cancer Immunotherapy. Cancer Res 2021, 81, 1201–1208. [Google Scholar] [CrossRef]
  158. Klichinsky, M.; Ruella, M.; Shestova, O.; Lu, X.M.; Best, A.; Zeeman, M.; Schmierer, M.; Gabrusiewicz, K.; Anderson, N.R.; Petty, N.E.; et al. Human chimeric antigen receptor macrophages for cancer immunotherapy. Nat. Biotechnol. 2020, 38, 947–953. [Google Scholar] [CrossRef]
  159. Ma, J.; Mo, Y.; Tang, M.; Shen, J.; Qi, Y.; Zhao, W.; Huang, Y.; Xu, Y.; Qian, C. Bispecific Antibodies: From Research to Clinical Application. Front. Immunol. 2021, 12. [Google Scholar] [CrossRef]
  160. Tian, Z.; Liu, M.; Zhang, Y.; Wang, X. Bispecific T cell engagers: An emerging therapy for management of hematologic malignancies. J. Hematol. Oncol. 2021, 14, 1–18. [Google Scholar] [CrossRef]
  161. Subklewe, M. BiTEs better than CAR T cells. Blood Adv. 2021, 5, 607–612. [Google Scholar] [CrossRef]
  162. Bahlis, N.J.; Raje, N.S.; Costello, C.; Dholaria, B.R.; Solh, M.M.; Levy, M.Y.; Tomasson, M.H.; Dube, H.; Liu, F.; Liao, K.H.; et al. Efficacy and safety of elranatamab (PF-06863135), a B-cell maturation antigen (BCMA)-CD3 bispecific antibody, in patients with relapsed or refractory multiple myeloma (MM). J. Clin. Oncol. 2021, 39, 8006. [Google Scholar] [CrossRef]
  163. Rodríguez-Otero, P.; D’Souza, A.; Reece, D.E.; van de Donk, N.W.; Chari, A.; Krishnan, A.Y.; Martin, T.G.; Mateos, M.-V.; Morillo, D.; Hurd, D.D.; et al. A novel, immunotherapy-based approach for the treatment of relapsed/refractory multiple myeloma (RRMM): Updated phase 1b results for daratumumab in combination with teclistamab (a BCMA x CD3 bispecific antibody). J. Clin. Oncol. 2022, 40, 8032. [Google Scholar] [CrossRef]
  164. Meermeier, E.W.; Welsh, S.J.; Sharik, M.E.; Du, M.T.; Garbitt, V.M.; Riggs, D.L.; Shi, C.-X.; Stein, C.K.; Bergsagel, M.; Chau, B.; et al. Tumor Burden Limits Bispecific Antibody Efficacy through T-cell Exhaustion Averted by Concurrent Cytotoxic Therapy. Blood Cancer Discov. 2021, 2, 354–369. [Google Scholar] [CrossRef] [PubMed]
  165. Philipp, N.; Kazerani, M.; Nicholls, A.; Vick, B.; Wulf, J.; Straub, T.; Scheurer, M.; Muth, A.; Hänel, G.; Nixdorf, D.; et al. T-cell exhaustion induced by continuous bispecific molecule exposure is ameliorated by treatment-free intervals. Blood 2022, 140, 1104–1118. [Google Scholar] [CrossRef] [PubMed]
  166. Caraccio, C.; Krishna, S.; Phillips, D.; Schürch, C.M. Bispecific Antibodies for Multiple Myeloma: A Review of Targets, Drugs, Clinical Trials, and Future Directions. Front. Immunol. 2020, 11, 501. [Google Scholar] [CrossRef]
  167. Gantke, T.; Reusch, U.; Kellner, C.; Ellwanger, K.; Fucek, I.; Weichel, M.; Kerber, A.; Peipp, M.; Treder, M. AFM26 is a novel, highly potent BCMA/CD16A-directed bispecific antibody for high affinity NK-cell engagement in multiple myeloma. J. Clin. Oncol. 2017, 35, 8045. [Google Scholar] [CrossRef]
  168. Watkins-Yoon, J.; Guzman, W.; Oliphant, A.; Haserlat, S.; Leung, A.; Chottin, C.; Ophir, M.; Vekeria, J.; Nelson, A.P.; Frye, Z.; et al. CTX-8573, an Innate-Cell Engager Targeting BCMA, is a Highly Potent Multispecific Antibody for the Treatment of Multiple Myeloma. Blood 2019, 134, 3182. [Google Scholar] [CrossRef]
  169. Chan, W.K.; Kang, S.; Youssef, Y.; Glankler, E.N.; Barrett, E.R.; Carter, A.M.; Ahmed, E.H.; Prasad, A.; Chen, L.; Zhang, J.; et al. A CS1-NKG2D Bispecific Antibody Collectively Activates Cytolytic Immune Cells against Multiple Myeloma. Cancer Immunol. Res. 2018, 6, 776–787. [Google Scholar] [CrossRef]
  170. Lancman, G.; Sastow, D.L.; Cho, H.J.; Jagannath, S.; Madduri, D.; Parekh, S.S.; Richard, S.; Richter, J.; Sanchez, L.; Chari, A. Bispecific Antibodies in Multiple Myeloma: Present and Future. Blood Cancer Discov. 2021, 2, 423–433. [Google Scholar] [CrossRef]
  171. Gantke, T.; Weichel, M.; Herbrecht, C.; Reusch, U.; Ellwanger, K.; Fucek, I.; Eser, M.; Müller, T.; Griep, R.; Molkenthin, V.; et al. Trispecific antibodies for CD16A-directed NK cell engagement and dual-targeting of tumor cells. Protein Eng. Des. Sel. 2017, 30, 673–684. [Google Scholar] [CrossRef]
  172. Park, A.J.; Santich, B.H.; Xu, H.; Lum, L.G.; Cheung, N.-K.V. Potent ex vivo armed T cells using recombinant bispecific antibodies for adoptive immunotherapy with reduced cytokine release. J. Immunother. Cancer 2021, 9, e002222. [Google Scholar] [CrossRef] [PubMed]
  173. Sanchez, L.; Wang, Y.; Siegel, D.S.; Wang, M.L. Daratumumab: A first-in-class CD38 monoclonal antibody for the treatment of multiple myeloma. J. Hematol. Oncol. 2016, 9, 1–8. [Google Scholar] [CrossRef] [PubMed]
  174. Naik, J.; Themeli, M.; Korlaar, R.D.J.; Ruiter, R.W.; Poddighe, P.J.; Yuan, H.; De Bruijn, J.D.; Ossenkoppele, G.J.; Zweegman, S.; Smit, L.; et al. CD38 as a therapeutic target for adult acute myeloid leukemia and T-cell acute lymphoblastic leukemia. Haematologica 2018, 104, e100–e103. [Google Scholar] [CrossRef] [PubMed]
  175. van de Donk, N.W.; Usmani, S.Z. CD38 Antibodies in Multiple Myeloma: Mechanisms of Action and Modes of Resistance. Front. Immunol. 2018, 9, 2134. [Google Scholar] [CrossRef]
  176. Overdijk, M.B.; Jansen, J.H.M.; Nederend, M.; Van Bueren, J.J.L.; Groen, R.; Parren, P.W.H.I.; Leusen, J.H.W.; Boross, P. The Therapeutic CD38 Monoclonal Antibody Daratumumab Induces Programmed Cell Death via Fcγ Receptor–Mediated Cross-Linking. J. Immunol. 2016, 197, 807–813. [Google Scholar] [CrossRef]
  177. Fionda, C.; Abruzzese, M.P.; Zingoni, A.; Cecere, F.; Vulpis, E.; Peruzzi, G.; Soriani, A.; Molfetta, R.; Paolini, R.; Ricciardi, M.R.; et al. The IMiDs targets IKZF-1/3 and IRF4 as novel negative regulators of NK cell-activating ligands expression in multiple myeloma. Oncotarget 2015, 6, 23609–23630. [Google Scholar] [CrossRef]
  178. Wang, Y.; Zhang, Y.; Hughes, T.; Zhang, J.; Caligiuri, M.A.; Benson, D.M.; Yu, J. Fratricide of NK Cells in Daratumumab Therapy for Multiple Myeloma Overcome by Ex Vivo–Expanded Autologous NK Cells. Clin. Cancer Res. 2018, 24, 4006–4017. [Google Scholar] [CrossRef]
  179. Vitkon, R.; Netanely, D.; Levi, S.; Ziv-Baran, T.; Ben-Yzak, R.; Katz, B.-Z.; Benyamini, N.; Trestman, S.; Mittelman, M.; Cohen, Y.; et al. Daratumumab in combination with proteasome inhibitors, rapidly decreases polyclonal immunoglobulins and increases infection risk among relapsed multiple myeloma patients: A single center retrospective study. Ther. Adv. Hematol. 2021, 12. [Google Scholar] [CrossRef]
  180. Terpos, E.; Gavriatopoulou, M.; Ntanasis-Stathopoulos, I.; Briasoulis, A.; Gumeni, S.; Malandrakis, P.; Fotiou, D.; Papanagnou, E.-D.; Migkou, M.; Theodorakakou, F.; et al. The neutralizing antibody response post COVID-19 vaccination in patients with myeloma is highly dependent on the type of anti-myeloma treatment. Blood Cancer J. 2021, 11, 1–9. [Google Scholar] [CrossRef]
  181. Dimopoulos, M.A.; Oriol, A.; Nahi, H.; San-Miguel, J.; Bahlis, N.J.; Usmani, S.Z.; Rabin, N.; Orlowski, R.Z.; Komarnicki, M.; Suzuki, K.; et al. Daratumumab, Lenalidomide, and Dexamethasone for Multiple Myeloma. N. Engl. J. Med. 2016, 375, 1319–1331. [Google Scholar] [CrossRef] [PubMed]
  182. Palumbo, A.; Chanan-Khan, A.; Weisel, K.; Nooka, A.K.; Masszi, T.; Beksac, M.; Spicka, I.; Hungria, V.; Munder, M.; Mateos, M.V.; et al. Daratumumab, Bortezomib, and Dexamethasone for Multiple Myeloma. N. Engl. J. Med. 2016, 375, 754–766. [Google Scholar] [CrossRef] [PubMed]
  183. Mateos, M.-V.; Sonneveld, P.; Hungria, V.; Nooka, A.K.; Estell, J.A.; Barreto, W.; Corradini, P.; Min, C.-K.; Medvedova, E.; Weisel, K.; et al. Daratumumab, Bortezomib, and Dexamethasone Versus Bortezomib and Dexamethasone in Patients With Previously Treated Multiple Myeloma: Three-year Follow-up of CASTOR. Clin. Lymphoma Myeloma Leuk. 2019, 20, 509–518. [Google Scholar] [CrossRef] [PubMed]
  184. Bahlis, N.J.; Dimopoulos, M.A.; White, D.J.; Benboubker, L.; Cook, G.; Leiba, M.; Ho, P.J.; Kim, K.; Takezako, N.; Moreau, P.; et al. Daratumumab plus lenalidomide and dexamethasone in relapsed/refractory multiple myeloma: Extended follow-up of POLLUX, a randomized, open-label, phase 3 study. Leukemia 2020, 34, 1875–1884. [Google Scholar] [CrossRef] [PubMed]
  185. Mateos, M.-V.; Dimopoulos, M.A.; Cavo, M.; Suzuki, K.; Jakubowiak, A.; Knop, S.; Doyen, C.; Lúcio, P.; Nagy, Z.; Kaplan, P.; et al. Daratumumab plus Bortezomib, Melphalan, and Prednisone for Untreated Myeloma. N. Engl. J. Med. 2018, 378, 518–528. [Google Scholar] [CrossRef]
  186. Moreau, P.; Attal, M.; Hulin, C.; Arnulf, B.; Belhadj, K.; Benboubker, L.; Béné, M.C.; Broijl, A.; Caillon, H.; Caillot, D.; et al. Bortezomib, thalidomide, and dexamethasone with or without daratumumab before and after autologous stem-cell transplantation for newly diagnosed multiple myeloma (CASSIOPEIA): A randomised, open-label, phase 3 study. Lancet 2019, 394, 29–38. [Google Scholar] [CrossRef]
  187. Facon, T.; Kumar, S.; Plesner, T.; Orlowski, R.Z.; Moreau, P.; Bahlis, N.; Basu, S.; Nahi, H.; Hulin, C.; Quach, H.; et al. Daratumumab plus Lenalidomide and Dexamethasone for Untreated Myeloma. N. Engl. J. Med. 2019, 380, 2104–2115. [Google Scholar] [CrossRef]
  188. Chari, A.; Suvannasankha, A.; Fay, J.W.; Arnulf, B.; Kaufman, J.L.; Ifthikharuddin, J.J.; Weiss, B.M.; Krishnan, A.; Lentzsch, S.; Comenzo, R.; et al. Daratumumab plus pomalidomide and dexamethasone in relapsed and/or refractory multiple myeloma. Blood 2017, 130, 974–981. [Google Scholar] [CrossRef]
  189. Dimopoulos, M.; Quach, H.; Mateos, M.-V.; Landgren, O.; Leleu, X.; Siegel, D.; Weisel, K.; Yang, H.; Klippel, Z.; Zahlten-Kumeli, A.; et al. Carfilzomib, dexamethasone, and daratumumab versus carfilzomib and dexamethasone for patients with relapsed or refractory multiple myeloma (CANDOR): Results from a randomised, multicentre, open-label, phase 3 study. Lancet 2020, 396, 186–197. [Google Scholar] [CrossRef]
  190. Dimopoulos, M.A.; Terpos, E.; Boccadoro, M.; Delimpasi, S.; Beksac, M.; Katodritou, E.; Moreau, P.; Baldini, L.; Symeonidis, A.; Bila, J.; et al. Daratumumab plus pomalidomide and dexamethasone versus pomalidomide and dexamethasone alone in previously treated multiple myeloma (APOLLO): An open-label, randomised, phase 3 trial. Lancet Oncol. 2021, 22, 801–812. [Google Scholar] [CrossRef]
  191. Van Bueren, J.L.; Jakobs, D.; Kaldenhoven, N.; Roza, M.; Hiddingh, S.; Meesters, J.; Voorhorst, M.; Gresnigt, E.; Wiegman, L.; Buijsse, A.O.; et al. Direct in Vitro Comparison of Daratumumab with Surrogate Analogs of CD38 Antibodies MOR03087, SAR650984 and Ab79. Blood 2014, 124, 3474. [Google Scholar] [CrossRef]
  192. Jiang, H.; Acharya, C.R.; An, G.; Zhong, M.; Feng, X.; Wang, L.; DaSilva, N.; Song, Z.; Yang, G.; Adrian, F.; et al. SAR650984 directly induces multiple myeloma cell death via lysosomal-associated and apoptotic pathways, which is further enhanced by pomalidomide. Leukemia 2015, 30, 399–408. [Google Scholar] [CrossRef]
  193. Attal, M.; Richardson, P.G.; Rajkumar, S.V.; San-Miguel, J.; Beksac, M.; Spicka, I.; Leleu, X.; Schjesvold, F.; Moreau, P.; Dimopoulos, M.A.; et al. Isatuximab plus pomalidomide and low-dose dexamethasone versus pomalidomide and low-dose dexamethasone in patients with relapsed and refractory multiple myeloma (ICARIA-MM): A randomised, multicentre, open-label, phase 3 study. Lancet 2019, 394, 2096–2107. [Google Scholar] [CrossRef]
  194. Moreau, P.; Dimopoulos, M.-A.; Mikhael, J.; Yong, K.; Capra, M.; Facon, T.; Hajek, R.; Špička, I.; Baker, R.; Kim, K.; et al. Isatuximab, carfilzomib, and dexamethasone in relapsed multiple myeloma (IKEMA): A multicentre, open-label, randomised phase 3 trial. Lancet 2021, 397, 2361–2371. [Google Scholar] [CrossRef]
  195. Tai, Y.-T.; Dillon, M.; Song, W.; Leiba, M.; Li, X.-F.; Burger, P.; Lee, A.I.; Podar, K.; Hideshima, T.; Rice, A.G.; et al. Anti-CS1 humanized monoclonal antibody HuLuc63 inhibits myeloma cell adhesion and induces antibody-dependent cellular cytotoxicity in the bone marrow milieu. Blood 2008, 112, 1329–1337. [Google Scholar] [CrossRef] [PubMed]
  196. Collins, S.M.; Bakan, C.E.; Swartzel, G.D.; Hofmeister, C.; Efebera, Y.A.; Kwon, H.; Starling, G.; Ciarlariello, D.; Bhaskar, S.S.; Briercheck, E.L.; et al. Elotuzumab directly enhances NK cell cytotoxicity against myeloma via CS1 ligation: Evidence for augmented NK cell function complementing ADCC. Cancer Immunol. Immunother. 2013, 62, 1841–1849. [Google Scholar] [CrossRef]
  197. Pazina, T.; James, A.M.; Colby, K.B.; Yang, Y.; Gale, A.; Jhatakia, A.; Kearney, A.Y.; Graziano, R.F.; Bezman, N.A.; Robbins, M.D.; et al. Enhanced SLAMF7 Homotypic Interactions by Elotuzumab Improves NK Cell Killing of Multiple Myeloma. Cancer Immunol. Res. 2019, 7, 1633–1646. [Google Scholar] [CrossRef]
  198. Kurdi, A.T.; Glavey, S.V.; Bezman, N.A.; Jhatakia, A.; Guerriero, J.L.; Manier, S.; Moschetta, M.; Mishima, Y.; Roccaro, A.; Detappe, A.; et al. Antibody-Dependent Cellular Phagocytosis by Macrophages is a Novel Mechanism of Action of Elotuzumab. Mol. Cancer Ther. 2018, 17, 1454–1463. [Google Scholar] [CrossRef]
  199. Hsi, E.D.; Steinle, R.; Balasa, B.; Szmania, S.; Draksharapu, A.; Shum, B.P.; Huseni, M.; Powers, D.; Nanisetti, A.; Zhang, Y.; et al. CS1, a Potential New Therapeutic Antibody Target for the Treatment of Multiple Myeloma. Clin. Cancer Res. 2008, 14, 2775–2784. [Google Scholar] [CrossRef]
  200. Campbell, K.S.; Cohen, A.D.; Pazina, T. Mechanisms of NK Cell Activation and Clinical Activity of the Therapeutic SLAMF7 Antibody, Elotuzumab in Multiple Myeloma. Front. Immunol. 2018, 9, 2551. [Google Scholar] [CrossRef]
  201. Awwad, M.H.S.; Mahmoud, A.; Bruns, H.; Echchannaoui, H.; Kriegsmann, K.; Lutz, R.; Raab, M.S.; Bertsch, U.; Munder, M.; Jauch, A.; et al. Selective elimination of immunosuppressive T cells in patients with multiple myeloma. Leukemia 2021, 35, 2602–2615. [Google Scholar] [CrossRef] [PubMed]
  202. Kikuchi, J.; Hori, M.; Iha, H.; Toyama-Sorimachi, N.; Hagiwara, S.; Kuroda, Y.; Koyama, D.; Izumi, T.; Yasui, H.; Suzuki, A.; et al. Soluble SLAMF7 promotes the growth of myeloma cells via homophilic interaction with surface SLAMF7. Leukemia 2019, 34, 180–195. [Google Scholar] [CrossRef] [PubMed]
  203. Lonial, S.; Dimopoulos, M.; Palumbo, A.; White, D.; Grosicki, S.; Spicka, I.; Walter-Croneck, A.; Moreau, P.; Mateos, M.V.; Magen, H.; et al. Elotuzumab Therapy for Relapsed or Refractory Multiple Myeloma. N. Engl. J. Med. 2015, 373, 621–631. [Google Scholar] [CrossRef]
  204. Dimopoulos, M.A.; Dytfeld, D.; Grosicki, S.; Moreau, P.; Takezako, N.; Hori, M.; Leleu, X.; Leblanc, R.; Suzuki, K.; Raab, M.S.; et al. Elotuzumab plus Pomalidomide and Dexamethasone for Multiple Myeloma. N. Engl. J. Med. 2018, 379, 1811–1822. [Google Scholar] [CrossRef] [PubMed]
  205. Chung, C. Role of Immunotherapy in Targeting the Bone Marrow Microenvironment in Multiple Myeloma: An Evolving Therapeutic Strategy. Pharmacother. J. Hum. Pharmacol. Drug Ther. 2017, 37, 129–143. [Google Scholar] [CrossRef]
  206. Lonial, S.; Lee, H.C.; Badros, A.; Trudel, S.; Nooka, A.K.; Chari, A.; Abdallah, A.-O.; Callander, N.; Lendvai, N.; Sborov, D.; et al. Belantamab mafodotin for relapsed or refractory multiple myeloma (DREAMM-2): A two-arm, randomised, open-label, phase 2 study. Lancet Oncol. 2019, 21, 207–221. [Google Scholar] [CrossRef]
  207. Berdeja, J.G.; Ailawadhi, S.; Niesvizky, R.; Wolf, J.L.; Zildjian, S.H.; O’Leary, J.; Chanan-Khan, A. Phase I Study of Lorvotuzumab Mertansine (IMGN901) In Combination with Lenalidomide and Dexamethasone In Patients with CD56-Positive Relapsed or Relapsed/Refractory Mulitple Myeloma - A Preliminary Safety and Efficacy Analysis of the Combination. Blood 2010, 116, 1934. [Google Scholar] [CrossRef]
  208. Yu, B.; Liu, D. Antibody-drug conjugates in clinical trials for lymphoid malignancies and multiple myeloma. J. Hematol. Oncol. 2019, 12, 1–17. [Google Scholar] [CrossRef]
  209. Kelly, K.R.; Siegel, D.S.; Chanan-Khan, A.A.; Somlo, G.; Heffner, L.T.; Jagannath, S.; Zimmerman, T.; Munshi, N.C.; Madan, S.; Mohrbacher, A.; et al. Indatuximab Ravtansine (BT062) in Combination with Low-Dose Dexamethasone and Lenalidomide or Pomalidomide: Clinical Activity in Patients with Relapsed / Refractory Multiple Myeloma. Blood 2016, 128, 4486. [Google Scholar] [CrossRef]
  210. Iida, S.; Ogiya, D.; Abe, Y.; Taniwaki, M.; Asou, H.; Maeda, K.; Uenaka, K.; Nagaoka, S.; Ishiki, T.; Conti, I.; et al. Dose-escalation study of tabalumab with bortezomib and dexamethasone in Japanese patients with multiple myeloma. Cancer Sci. 2016, 107, 1281–1289. [Google Scholar] [CrossRef]
  211. Kaufman, J.L.; Niesvizky, R.; Stadtmauer, E.A.; Chanan-Khan, A.; Siegel, D.; Horne, H.; Wegener, W.A.; Goldenberg, D.M. Phase I, multicentre, dose-escalation trial of monotherapy with milatuzumab (humanized anti-CD74 monoclonal antibody) in relapsed or refractory multiple myeloma. Br. J. Haematol. 2013, 163, 478–486. [Google Scholar] [CrossRef] [PubMed]
  212. Voorhees, P.M.; Manges, R.F.; Sonneveld, P.; Jagannath, S.; Somlo, G.; Krishnan, A.; Lentzsch, S.; Frank, R.C.; Zweegman, S.; Wijermans, P.W.; et al. A phase 2 multicentre study of siltuximab, an anti-interleukin-6 monoclonal antibody, in patients with relapsed or refractory multiple myeloma. Br. J. Haematol. 2013, 161, 357–366. [Google Scholar] [CrossRef] [PubMed]
  213. Lesokhin, A.M.; Ansell, S.M.; Armand, P.; Scott, E.C.; Halwani, A.; Gutierrez, M.; Millenson, M.M.; Cohen, A.D.; Schuster, S.J.; Lebovic, D.; et al. Nivolumab in Patients With Relapsed or Refractory Hematologic Malignancy: Preliminary Results of a Phase Ib Study. J. Clin. Oncol. 2016, 34, 2698–2704. [Google Scholar] [CrossRef] [PubMed]
  214. Ansell, S.; E Gutierrez, M.; Shipp, M.A.; Gladstone, D.; Moskowitz, A.; Borello, I.; Popa-McKiver, M.; Farsaci, B.; Zhu, M.L.; Lesokhin, A.M.; et al. A Phase 1 Study of Nivolumab in Combination with Ipilimumab for Relapsed or Refractory Hematologic Malignancies (CheckMate 039). Blood 2016, 128, 183. [Google Scholar] [CrossRef]
  215. Usmani, S.Z.; Schjesvold, F.; Oriol, A.; Karlin, L.; Cavo, M.; Rifkin, R.M.; Yimer, H.A.; LeBlanc, R.; Takezako, N.; McCroskey, R.D.; et al. Pembrolizumab plus lenalidomide and dexamethasone for patients with treatment-naive multiple myeloma (KEYNOTE-185): A randomised, open-label, phase 3 trial. Lancet Haematol. 2019, 6, e448–e458. [Google Scholar] [CrossRef]
  216. Cho, H.J.; Costa, L.J.; Davies, F.E.; Neparidze, N.; Vij, R.; Feng, Y.; Teterina, A.; Fritsch, E.W.; Wenger, M.; Kaufman, J.L. Atezolizumab in Combination with Daratumumab with or without Lenalidomide or Pomalidomide: A Phase Ib Study in Patients with Multiple Myeloma. Blood 2018, 132, 597. [Google Scholar] [CrossRef]
  217. Armand, P.; Lesokhin, A.; Borrello, I.; Timmerman, J.; Gutierrez, M.; Zhu, L.; McKiver, M.P.; Ansell, S.M. A phase 1b study of dual PD-1 and CTLA-4 or KIR blockade in patients with relapsed/refractory lymphoid malignancies. Leukemia 2020, 35, 777–786. [Google Scholar] [CrossRef]
Figure 1. Multiple myeloma and asymptomatic precursor states. MM is preceded in virtually all cases by the asymptomatic precursor states monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). The international myeloma working group (IMWG) defines asymptomatic MM as having ≥1 myeloma defining events with either clonal BM plasma cells ≥10% or biopsy proven plasmacytoma.
Figure 1. Multiple myeloma and asymptomatic precursor states. MM is preceded in virtually all cases by the asymptomatic precursor states monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). The international myeloma working group (IMWG) defines asymptomatic MM as having ≥1 myeloma defining events with either clonal BM plasma cells ≥10% or biopsy proven plasmacytoma.
Curroncol 29 00705 g001
Figure 2. Timeline of treatment advancements in multiple myeloma.
Figure 2. Timeline of treatment advancements in multiple myeloma.
Curroncol 29 00705 g002
Table 1. Summary of CAR T-Cell Clinical Trials in MM.
Table 1. Summary of CAR T-Cell Clinical Trials in MM.
Product
(Trial Name)
Target
(Costim Domain)
PhaseStudy PopulationResponse and OutcomesGrade ≥3 CRS
(Grade ≥3 NTX)
PMID
(NCT)
FDA approved
Ide-cel
(KarMMa)
BCMA
(4-1BB)
2;
FDA approved
RRMMORR: 73%; mPFS: 12.1 months at 450 × 106 target dose6%
(3%)
PMID: 33626253
(NCT03361748)
Cilta-cel (CARTITUDE-1)BCMA
(4-1BB)
1b/2;
FDA approved
RRMMORR: 97%; mPFS and mOS not reached5.1%
(12.3%)
PMID: 35658469
(NCT04133636)
BCMA CAR T-cell trials with reported data
CAR-BCMA
first-in-human trial
BCMA
(CD28)
1RRMMORR: 81%; mPFS: 7.8 months25%
(4%)
PMID: 27412889
(NCT02215967)
CART-BCMABCMA
(4-1BB)
1RRMMORR: 48%; mPFS: 2.7 months32%
(12%)
PMID: 30896447
(NCT02546167)
Ide-cel + PI3K inhibitor
(CRB-402)
BCMA
(4-1BB)
1RRMMORR: 55% (≥CR: 18%)4.3%
(6.5%)
(NCT03274219)
Cilta-cel (CARTITUDE-2)BCMA
(4-1BB)
2RRMM and NDMMORR: 88.9% (≥ CR: 27.8%)NA(NCT4133636)
Zevor-cel
(LUMMICAR-1)
BCMA
(4-1BB)
1RRMMORR: 87.5%; mDOR: 21.8 months0%
(0%)
(NCT03975907)
Zevor-cel
(LUMMICAR-2)
BCMA
(4-1BB)
1b/2RRMMORR: 100%0%
(0%)
(NCT03915184)
Zevor-celBCMA
(4-1BB)
1RRMMORR: 87.5%; mPFS not reached0%
(4%)
(NCT03302403)
(NCT03716856)
(NCT03380039)
C-CAR088BCMA
(4-1BB)
1RRMMORR: 95.2%; mPFS not reached5%
(0%)
(NCT04322292)
(NCT03815383)
(NCT03751293)
(NCT04295018)
Single-domain antibody CARBCMA
(4-1BB)
1RRMMORR: 88.2%; mPFS 12.1 months;2.9%
(0%)
(NCT03661554)
FCARH143BCMA
(4-1BB)
1RRMMORR: 100%; mPFS not reached0%
(0%)
(NCT03338972)
Orva-cel
(EVOLVE)
BCMA
(4-1BB)
1/2RRMMORR: 91%; mPFS not reached2%
(4%)
(NCT03430011)
MCARH171BCMA
(4-1BB)
1RRMMORR: 64%; mPFS not reached20%
(0%)
(NCT03070327)
FHVH33BCMA
(4-1BB)
1RRMMORR: 80%7%(NCT03602612)
LCAR-B38MBCMA
(4-1BB)
1RRMMORR: 88.2%; 12-month PFS: 52.9%41.2%
(0%)
(NCT03090660)
LCAR-B38M
(LEGEND-2)
BCMA
(4-1BB)
1/2RRMMORR: 88%; mPFS: 15 months7%
(0%)
PMID: 30572922
(NCT03090659)
tEGFR suicide switch CARBCMA
(4-1BB)
1RRMMORR: 86%; mPFS not reached0%
(0%)
(NCT03093168)
KITE-585BCMA
(CD28)
1RRMMORR: 100%; mPFS 1 month at 1 × 109 dose0%
(0%)
PMID: 34249462
(NCT03318861)
Equecabtagene Autoleucel
(FUMANBA-1)
BCMA1/2RRMMORR: 94.9% (≥CR: 68.4%)0%
(0%)
ChiCTR1800018137
(NCT05066646)
P-BCMA-101 (PRIME)BCMA
(4-1BB)
1/2RRMMORR: 57%; mPFS not reached2%
(0%)
(NCT03288493)
CTL119BCMA, CD19
(4-1BB)
1High-risk MMORR: 80%0%(NCT03549442)
CART-19/BCMA (cocktail)BCMA, CD19
(OX40/CD28)
1/2High-risk NDMMORR: 100%; mPFS not reached0%
(0%)
PMID: 35114022
(NCT03455972)
SZ-MM-CART01BCMA, CD19, CD138
(OX40/CD28)
1RRMMORR: 100%34%(NCT03196414)
ARC-101BCMA
(4-1BB)
1RRMMORR: 100%4.8%
(0%)
(NCT04155749)
ALLO-715BCMA1RRMMORR: 60% in 320 × 106 dose0%
(0%)
(NCT04093596)
CAR T cells against other targets
CTL019CD19
(4-1BB)
1RRMMORR: 80%0%
(0%)
PMID: 29669947
(NCT02135406)
Tisa-celCD192RRMMNANA(NCT02794246)
VariousSLAMF71/2RRMMNANA(NCT03710421)
(NCT04142619)
(NCT04541368)
(NCT03958656)
(NCT04499339)
MCARH109GPRC5D1RRMMORR: 71%; mPFS not reached6%
(6%)
PMID: 36170501
(NCT04555551)
VariousGPRC5D1RRMMNANA(NCT05219721)
(NCT05016778)
CAR T-138CD138
(4-1BB)
1/2RRMMORR: 80%0%
(0%)
(NCT01886976)
ALTCAR.CD138CD1381RRMMNANA(NCT03672318)
CAR2 Anti-CD38 A2 CAR T CellsCD381RRMMNANA(NCT03464916)
CM-CS1 T cell infusionNKG2D
(Dap10)
1RRMMORR: 0%0%
(0%)
PMID: 30396908
(NCT02203825)
NKR-2 (CYAD-01)
(THINK)
NKG2D1/2RRMMORR: 0%NA(NCT03018405)
CAR T-TnMUC1Tn-MUC11RRMMNANA(NCT04025216)
MLM-CAR44.1 T cellsCD44v61/2RRMMNANA(NCT04097301)
OPC-415MMG491/2RRMMNANA(NCT04649073)
Dual-Targeting CAR T cells
GC012FBCMA and CD191RRMMORR: 93.8% at 3 × 105/kg dose7.1%(NCT04236011)
(NCT04182581)
VariousBCMA and CD191RRMMNANA(NCT04412889)
(NCT04795882)
(NCT04162353)
(NCT03706547)
(NCT04714827)
AUTO2BCMA and TACI1/2RRMMORR: 43%0%
(0%)
(NCT03287804)
VariousBCMA and TACI1RRMMNANA(NCT05020444)
(NCT04657861)
VariousBCMA and SLAMF71RRMMNANA(NCT04662099)
(NCT04156269)
NABCMA and CD381/2RRMMNANA(NCT03767751)
Table 2. Summary of BiTE Clinical Trials in MM.
Table 2. Summary of BiTE Clinical Trials in MM.
Product
(Trial Name)
TargetPhaseStudy PopulationResponse and OutcomesGrade ≥3 CRS
(Grade ≥3 NTX)
PMID
(NCT)
BCMA BiTE trials with reported data
Elranatamab
(MagnetisMM-1)
BCMA1RRMMORR:75%; mPFS: not published0%
(0%)
(NCT03269136)
Teclistamab or talquetamab + daratumumab
(TRIMM-2)
BCMA or GPRC5D1RRMMORR: 78%; mPFS: not published0%
(0%)
(NCT04108195)
PacanalotamabBCMA1RRMMORR 70; mPFS: 23.52%
(4%)
PMID: 31895611
(NCT02514239)
AlnuctamabBCMA1RRMMORR 83%; mPFS: not published5%
(0%)
NCT03486067
TNB-383BBCMA1RRMMORR 52%; mPFS: not published0%
(0%)
NCT03933735
REGN5458
(LINKER-MM1)
BCMA1/2RRMMORR 60%; mPFS: not published0%
(0%)
NCT03761108
Pavurutamab + pomalidomide
(ParadigMM-1B)
BCMA1/2RRMMORR 82%; mPFS: not published7%
(0%)
NCT03287908
Teclistamab
(MajesTEC-1)
BCMA2RRMMORR 65%; mPFS: not published0%
(0%)
NCT04557098
Non-BCMA BiTE trials
Talquetamab
(MonumenTAL-1)
GPRC5D1RRMMOR: 63%; mPFS not Published4%
(0%)
NCT03399799
Talquetamab + anticancer drugs
(MonumenTAL-2)
GPRC5D1RRMMNANANCT05050097
TalquetamabGPRC5D1RRMMNANANCT04773522
TalquetamabGPRC5D2RRMMNANANCT04634552
BlinatumomabCD191RRMMNANANCT03173430
AMG 424CD381RRMMNANANCT03445663
Y150CD381RRMMNANANCT05011097
GBR1342CD381RRMMNANANCT03309111
Cevostamab
(CAMMA 1)
FcRH51RRMMNANANCT04910568
CevostamabFcRH51RRMMORR: 52%; mPFS not reached2%
(0%)
NCT03275103
Table 3. Summary of Major Clinical Trials Leading to FDA Approval of Daratumumab.
Table 3. Summary of Major Clinical Trials Leading to FDA Approval of Daratumumab.
Trial NameInterventionStudy PopulationMedian Progression Free Survival
(Months)
Overall Response Rate
(Percent)
Median Overall Survival
Daratumumab for Treatment of Relapsed or Refractory Multiple Myeloma
SIRIUSDara monotherapy≥2–3 lines of therapy including PI and IMiD3.729.21-year: 65%
CASTORDara-Vd versus Vd≥1 lines of therapy with response and progression16.7 versus 7.183.0 versus 63.0NR (at 3 years: 61% vs. 51%)
POLLUXDara-Rd versus Rd≥1 lines of therapy with response and progression44.5 versus 17.592.9 versus 76.4NR (at 42 months: 65% vs. 57%)
APOLLODara-Pd versus Pd≥1 lines of therapy including lenalidomide and a proteasome inhibitor12.4 versus 6.9N/A (at 16.9 months 69 versus 46)Overall survival data were not mature
CANDORDara-Kd versus Kd1–3 lines of prior therapyNR versus 15.884.3 versus 74.7NR
Daratumumab for Treatment of Newly Diagnosed Multiple Myeloma
MAIADara-Rd versus RdNewly diagnosed transplant-ineligible multiple myelomaNR versus 33.892.9 versus 81.3NR
ALCYONEDara-VMP versus VMPNewly diagnosed transplant-ineligible multiple myeloma36.9 versus 19.390.9 versus 73.9NR
CASSIOPEIADara-VTd versus VTdNewly diagnosed transplant eligible multiple myelomaNR vs. 46.7 monthssCR 29 vs 20NR
GRIFFINDara-VRd versus VRdNewly diagnosed transplant eligible multiple myelomaNR (at 24 months: 95.8 vs. 89.8)sCR 42 vs 34Overall survival data were not mature
Table 4. Summary of Major Clinical Trials Leading to FDA Approval of Isatuximab.
Table 4. Summary of Major Clinical Trials Leading to FDA Approval of Isatuximab.
Trial NameInterventionStudy PopulationMedian Progression Free Survival (Months)Overall Response Rate
(Percent)
Median Overall Survival
ICARIA-MMIPd versus Pd≥2 prior lines including IMid and PI11.5 vs. 6.560.4 versus 35.3At 12 months: 72% versus 63%
IKEMAIKd versus Kd1–3 lines of prior therapy, no prior carfilzomibNR vs. 19.287 versus 83Overall survival data were not mature
Table 5. Summary of Major Clinical Trials for FDA Approval of Elotuzumab.
Table 5. Summary of Major Clinical Trials for FDA Approval of Elotuzumab.
Trial NameInterventionStudy PopulationMedian Progression Free Survival (Months)Overall Response Rate
(Percent)
Median Overall Survival
ELOQUENT-2ERd versus Rd≥1 lines of therapy19.4 vs. 14.979% vs. 66%NR
ELOQUENT-3EPd versus Pd≥2 lines of therapy therapies, including lenalidomide and a proteasome inhibitor10.25 vs. 4.6753.3% vs. 26.3%NR
Table 6. Summary of Major Clinical Trials for FDA Approval of Belantamab.
Table 6. Summary of Major Clinical Trials for FDA Approval of Belantamab.
Trial NameInterventionStudy PopulationMedian Progression Free Survival (Months)Overall Response Rate
(Percent)
Median Overall Survival
Dreamm-2Belantamab≥4 prior therapies, including an anti-CD38 monoclonal antibody, a proteasome inhibitor, and an immunomodulatory agent5.731NR
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Ho, M.; Xiao, A.; Yi, D.; Zanwar, S.; Bianchi, G. Treating Multiple Myeloma in the Context of the Bone Marrow Microenvironment. Curr. Oncol. 2022, 29, 8975-9005. https://doi.org/10.3390/curroncol29110705

AMA Style

Ho M, Xiao A, Yi D, Zanwar S, Bianchi G. Treating Multiple Myeloma in the Context of the Bone Marrow Microenvironment. Current Oncology. 2022; 29(11):8975-9005. https://doi.org/10.3390/curroncol29110705

Chicago/Turabian Style

Ho, Matthew, Alexander Xiao, Dongni Yi, Saurabh Zanwar, and Giada Bianchi. 2022. "Treating Multiple Myeloma in the Context of the Bone Marrow Microenvironment" Current Oncology 29, no. 11: 8975-9005. https://doi.org/10.3390/curroncol29110705

Article Metrics

Back to TopTop