Why Immunotherapy Fails in Multiple Myeloma
Abstract
:1. Introduction
2. Monoclonal Antibodies
2.1. Anti-CD38
- Complement-dependent cytotoxicity (CDC): Binding between the Fc tail of the antibody and C1q activates the complement cascade to end with the formation of the membrane attack complex (MAC) [72];
- Antibody-dependent cell-mediated cytotoxicity (ADCC): Binding between FC-gamma receptors on effector cells (T and NK cells) and the Fc tail of daratumumab releases cytotoxic molecules, leading to MM cell death [65];
- Antibody-dependent cellular phagocytosis (ADCP): Opsonization of the tumor cell occurs when the Fc tail of the CD38 antibody binds to the Fc-gamma receptor of phagocytic cells such as monocytes or macrophages [73];
- CD38 expression: Tests performed on modified MM cell lines that express different levels of CD38 have shown greater CDC and ADCC in cells expressing high levels of CD38 compared to cells with low expression. In MM plasma cells, expression is heterogenic and daratumumab activity is correlated with such expression levels [78]. Analysis performed on samples of patients who had been enrolled in daratumumab clinical trials showed a quick and marked decrease in CD38 levels after treatment in all patients; a decrease in CDC and ADCC was also observed in ex vivo tests. Downregulation of CD38 of this type also occurs in cell subsets other than MM cells and mechanisms are not fully understood. Some strategies to overcome such resistance have been proposed and are based on combinations with other drugs capable of increasing CD38 levels such as IMiDs, panobinostat, all-trans retinoic acid (ATRA), and ricolinostat [79,80,81]. The ability of ATRA to resynthesize CD38 is being analyzed in a clinical trial (NCT02751255);
- Complement inhibitory proteins: Tumor cells are known to be capable of increasing soluble and membrane-bound complement regulatory proteins such as C4-binding protein, CD55, or CD59 to protect themselves from complement attacks, similar to the way in which immune checkpoint inhibitor receptors function [82]. Ex vivo analysis using MM cell lines with low expression of CD55 and CD59, and MM cell lines treated with phospholipase-C to remove GPI-anchored proteins (CD55 and CD59) showed increased daratumumab CDC. These observations were not confirmed with MM cells obtained from daratumumab-naïve patients. In addition, an increase in CD55 and CD59 expression was detected in MM cells obtained from patients who were progressing under monotherapy treatment. In this case, ATRA combination may also decrease upregulation of complement inhibitors [78]. Panobinostat, which has shown to increase CD38 levels, also increases CD55 and CD59 levels, possibly explaining the lack of benefit in terms of CDC, although ADCC improved [83];
- CD47-SIRPα interaction: CD47 expressed in tumor cells of solid tumors and hematological malignancies interacts with regulatory transmembrane protein SIRPα that is expressed on dendritic cells and macrophages, decreasing their phagocytic function [84]. Upregulation of CD47 has been observed in drug-resistant MM cells and blocking the interaction between SIRPα and CD47 restores phagocytosis [85]. Anti-CD47 therapies are under evaluation in other lymphoid malignancies and low-dose cyclophosphamide may decrease CD47 expression to improve ADCP [86,87,88];
- Polymorphisms on Fc-gamma receptors: Mechanism of action of daratumumab ADCC and ADCP depend on the activation of Fc-gamma receptors on effector cells [89]. Affinity may differ based on allelic variants of these receptors. Fc-gamma receptors were genotyped in samples of patients with MM included in daratumumab clinical trials, demonstrating a positive correlation between polymorphisms 3A and 2B and outcome in terms of PFS, albeit not OS [90];
- The way in which the microenvironment plays a crucial role in MM has been well studied. Bone marrow stromal cells (BMSC) protect MM cells from drugs and effector cells such as cytotoxic T cells [91]. Interaction between BMSC and MM cells may upregulate anti-apoptotic molecules like survivin, which could contribute to resistance against daratumumab;
- Soluble CD38 (sCD38) may have a draining effect on daratumumab function and diminish efficacy; however, the presence of sCD38 has been observed in only a few patients and in such cases, did not correlate with response. There are no published data about other CD38 antibodies and the impact of sCD38 [82];
- NK cells play a crucial role in ADCC. Some studies have shown a correlation between daratumumab-induced ADCC and NK cell-to-MM cell ratio [78]. Due to their capacity to activate NK cells, IMiDs could improve NK function and ADCC, even in patients with IMiD-refractory MM [65,92]. An increase in ADCC was observed in ex vivo experiments when interaction between NK inhibitory receptors KIR (KIR2DL-1, -2, -3) and their respective ligands was blocked. Similarly, ADCC was reported to improve synergistically with the addition of lenalidomide to the experiment. As NK cells express CD38 on their surface, fratricide and a diminished effector function can arise. When studied in patients, the reduction in NK levels was similar in responders and non-responders to daratumumab and no correlation with outcome was observed. Some measures have nonetheless been proposed to diminish this eventual effect, including the administration of ex vivo-expanded autologous NK cells to increase the count, and pretreatment of such cells with F(ab’)2 fragments of daratumumab to avoid fratricide [93,94].
Mechanisms of Action | Mechanisms of Resistance |
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2.2. Anti-SLAMF7
3. Antibody-Drug Conjugate
4. Bispecific Monoclonal Antibodies
5. Immune Checkpoint Inhibitors
6. Chimeric Antigen Receptor T Cell Therapy
6.1. Mechanisms or Relapse
6.1.1. Antigen-Positive Escape
6.1.2. Antigen-Negative Escape
6.2. CAR T Cell-Related Toxicities
6.3. Product Manufacturing, Access and Economic Challenges
7. Vaccines
8. Personal Perspective
9. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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---|---|---|---|---|---|---|
Monoclonal antibodies | CD38 | First-in-human, phase I/II. Monotherapy 16 mg/kg [25,26] | ≥3 | ORR 31.1% sCR 4.7% | PFS 4 mo OS 20.1 mo | IRR 48% (2.7% ≥ grade 3) |
GEN 503. Part 2: dose expansion with DRd [27,28] | 2 | ORR 81% sCR 25% | PFS 72% OS 90% | IRR 56% (6.3% ≥ grade 3) | ||
POLLUX phase III DRd vs. Rd. R refractory were excluded [29] | 1 | CR 43.1 vs. 19.2% (p < 0.001) sCR 22.4 vs. 4.6% (p < 0.001) (DRd vs. Rd) | 12 m PFS 83.2 vs. 60.1% OS 91.2 vs. 76.4% (p < 0.001) | IRR 47.7% (6.3% ≥ grade 3); 92% occurring during the first infusion | ||
CASTOR phase III DVd [30,31] | 2 | ORR 83.8 vs. 63.2% (p < 0.0001) CR or better 28.8 vs. 9.8% (p < 0.0001) sCR 8.8 vs. 2.6% (DVd vs. Vd) | 18 m PFS 48 vs. 7.9% In high-risk cytogenetics PFS 11.2 vs. 7.2% | IRR 45.3% (8.3% ≥ grade 3) | ||
SLAMF7/CS-1 | E monotherapy. Phase I, dose escalation 0.5–20 mg/kg [32] | ≥2 | No maximum tolerated dose ORR 0% SD 26.5% | NA | IRR 52% before the initiation of prophylaxis | |
Vd +/− E, randomized phase II [33] | ≥1 | ORR 65 vs. 63% CR 4 vs. 4% (EVd vs. Vd) | PFS 9.7 vs. 6.9 mo OS 85 vs. 74% | IRR 7% (0% ≥ grade 3) | ||
ELOQUENT-2 Rd +/− E, randomized phase III [34] | 1–3 | ORR 79 vs. 66% (p = 0.0002) (ERd vs. Rd) | 3 y PFS (3y) 26 vs. 18% 3 y-OS 60 vs. 53% (p = 0.026) | Comparable between groups | ||
Pd +/− E, randomized phase II [35] | ≥2 | ORR 53 vs. 26% (EPd vs. Pd) | PFS 10.3 vs. 4.7 mo | IRR 5% (0% ≥ grade 3) | ||
ADC | BCMA | GSK-2857916 conjugated to MMAF; phase I [36,37] | ≥3 | ORR 60% CR 9% sCR 6% | PFS 12 mo | Thrombocytopenia 35% Eye-related events: Blurry vision 52%, dry eyes 37%, photophobia 29% |
CD138 | Indatuximab ravtansine linked to maytansinoid; phases I/II [38,39] | ≥2 | ORR 5.9% CR 0% SD 42.9% | PFS 3 mo | Fatigue 47% Diarrhea 43% | |
CD56 | Lorvotuzumab-mertansine; phase I [40] | ≥1 | ORR 5.7% CR 0% SD 42.9% | PFS 26.1 weeks in evaluable | Peripheral neuropathy 5.3% | |
CD74 | Milatuzumab doxorubicin; phase I [41] | ≥2 | No objective responses. SD 5/19 (26%) for 3 mo | NA | n = 1 grade 3 IRR | |
Bispecific antibodies | BCMA/CD3 | AMG 420: First-in-human, phase I, dose escalation: maximum tolerated 400 µg/day. No extramedullary disease [42,43] | ≥2 | Dose 400 µg/day ORR 70% sCR 50% | Dose 400 µg/day PFS 9 mo | CRS 38.1% (grade ≥ 3 7.1%) Dose-limiting peripheral neuropathy n = 2 |
Teclistamab; phase I; dose range: 0.3–270 µg/kg [44] | 6 | ORR 78% in patients receiving highest dose | - | CRS 56% (all grade 1/2) Neurotoxicity 8% (3% grade ≥ 3) IRR 9% | ||
Immune checkpoint inhibitors | PD-1 | Nivolumab monotherapy; phase I including several neoplasms [45] | ≥1 | ORR 4% SD 63% | - | Drug-related AEs 52% any grade, 19% ≥ grade 3 |
KEYNOTE-183; phase III, randomized Pd +/− Pembrolizumab [46] | ≥2 | ORR 34 vs. 40% (Pembrolizumab + Pd vs. Pd) | PFS 5.6 vs. 8.4 (median time to progression 8.1 vs. 8.7 mo) (Pembrolizumab + Pd vs. Pd) | Serious AE 63 vs. 46% (Pembrolizumab + Pd vs. Pd) TRM n = 4: unknown cause, neutropenic sepsis, myocarditis, Stevens–Johnson syndrome | ||
KEYNOTE-185; phase III, randomized Rd +/− Pembrolizumab [46] | Newly-diagnosed ASCT ineligible | ORR 64 vs. 62% (Pembrolizumab + Rd vs. Rd) | PFS not reached | Serious AE 54 vs. 39% (Pembrolizumab + Rd vs. Rd) Terminated because of the uneven number of deaths between groups | ||
CAR T cell | BCMA | NCI scFv murine/CD28 [47] | 9.5 | ORR 81% (≥CR 13%) | mEFS 7.2 mo | CRS 94% (grade ≥ 3 38%) ICANS NA (grade ≥ 3 19%) |
UPenn/CART-BCMA scFv human/4-1BB [48] | 7 | ORR 64% (≥CR 11%) | mPFS 4.2 mo | CRS 88% (grade ≥ 3 32%) ICANS 32 (grade ≥ 3 12%) | ||
LCAR-B38M VHH llama/4-1BB [49,50] | 3 | ORR 88% (≥CR 74%) | mPFS 20 mo18 m OS 68% | CRS 89% (grade ≥ 3 7%) ICANS 2 (grade ≥ 3 0%) | ||
LCAR-B38M VHH llama/4-1BB [51] | 4 | ORR 88% (≥CR 77%) | 1 y PFS 53%1 y OS 82% | CRS 100% (grade ≥ 3 41%) ICANS NA (grade ≥ 3 NA) | ||
Ciltacabtagene Autolecuel (LCAR-B38M/JNJ68284528) CARTITUDE-1 [52] | 6 | ORR 97% (sCR 67%) | 1 y PFS 76.6% 1 y OS 88.5% | CRS 95% (grade ≥ 3 4%) ICANS 21% (grade ≥ 3 10%) | ||
Idecabtagene Vicleucel (bb2121)/scFv murine/4-1BB [24] | 7–8 | ORR 85% (≥CR 45%) | mPFS 11.8 mo | CRS 76% (grade ≥ 3 6%) ICANS 42% (grade ≥ 3 3%) | ||
Idecabtagene Vicleucel (bb2121)/scFv murine/4-1BB KarMMA [53] | 6 | ORR 73% (≥CR 33%) | mPFS 8.8 mo mOS 19.4 mo | CRS 84% (grade ≥ 3 6%) ICANS 18% (grade ≥ 3 3%) | ||
Orvacabtagene Autoleucel (JCARH125)/scFv human 4-1BB EVOLVE [54] | 6 | ORR 92% (≥CR 36%) | mPFS 9.3 mo | CRS 89% (grade ≥ 3 3%) ICANS 13% (grade ≥ 3 3%) | ||
Vaccines | Dendritic cells/tumor fusions | Vaccine composed of autologous dendritic cells and patient-derived myeloma cells; 16 patients included [55] | 4 | SD: 11 | - | Site reaction (grade 1) |
hTERT/Survivin | NCT00499577 [56] | 1 | IR 36% | mEFS 20 mo | Chills 57% Rash > 85% (grades 1–2) | |
Dendritic cells/tumor fusions | Two cohorts: 24 patients vaccinated post-ASCT 12 patients vaccinated pre- and post- ASCT [57] | - | ORR 78% (CR 47%) | 2 y PFS 57% | Site reaction (grade 1) Myalgia (grade 1) | |
MAGE-A3 | NCT01245673 [58] | 1–5 | IR 88% | 2 y OS 74% 2 y EFS 56% | Site reaction >90 % | |
XBP1 CD138 CS1 | NCT01718899: SMM patients; two cohorts: Monotherapy Combination with IMiDs [59] | 1 | IR 95% | mTTP: 36 w mTTP: not reached | Site reaction 58–100% (grades 1–2) | |
MAGE-A3 | NCT01380145: vaccinated post ASCT [60] | 1–2 | IR 100% | mPFS 27 mo mOS not reached | Site reaction 54% (grade 1)Myalgia 33% (grades 1–2) |
Limitation | Rationale | Approach |
---|---|---|
Antigen-positive escape | Impaired T cell persistence | Optimize CAR design (human scFv, hinge, costimulatory domains) to avoid antigen-independent tonic signaling and reduce antigenicity Younger T cell donors, transduction to stem cell memory T cell and central memory T cells, block T cell differentiation signaling, or use of non-viral transduction systems Genomic knock-in of the CAR sequence to the TRAC locus |
Impaired T cell potency | Fine-tuning CAR design (human scFv, hinge, costimulatory domains) Avoid antigen-independent tonic signaling Genomic knock-in of the CAR sequence to the TRAC locus Avoid T cell exhaustion (combine with immune check-point inhibitors or disrupt the checkpoint pathway) Reduce the amount of soluble target antigen Optimize lymphodepletion protocol | |
Tumor microenvironment-induced immunosuppression | Boost T cell trafficking and migration Overcome inhibitory signals by blocking immune check-point pathways or switching inhibitory signals present in the TME into pro-inflammatory signals Targeting immunosuppressive immune cells (regulatory T cells, tumor-associated macrophages, myeloid-derived suppressor cells) Armored CAR T cells or TRUCKs | |
Antigen-negative escape | Immune selection pressure Gene mutations Lineage switching Trogocytosis Antigen masking | Identification and selection of the most suitable tumor antigen Fine-tuning antigen binding affinity Targeting multiple tumor antigens (sequential or co-administration of single-target CAR products, dual CARs, or tandem CARs) Upregulate surface density of the target antigen Targeting myeloma stem cells |
Toxicities | CRS and ICANS | Optimizing reduction in the number of CAR T cells infused or dividing doses on different days Prompt recognition with the use of predictive biomarkers Use of tocilizumab or corticosteroids in early stages of the disease Tailored modifications of the construct, optimizing the costimulatory domain CAR T cells with suicide genes or “OFF-switches” |
On-target, off-tumor | Affinity tuning of the scFv Advanced CAR engineering: “AND” logic-gate, “ON-switch”, “SPLIT”, or inhibitory CARs | |
Manufacturing | Amount and quality of T cells Vein-to-vein time Production failure | Allogeneic CAR T cells (major concerns: GvHD and CAR T cell rejection) |
Access and economic | Infrastructure, workflows, processes, regulatory requirements, and economic burden | Cooperation among multiple stakeholders Use of non-viral gene delivery with transposon/transposase systems Creation of community CAR T cell therapy centers Promote the outpatient setting Shift from centralized to decentralized manufacturing, namely “bedside manufacturing” Cost-effectiveness, cost-benefit, and quality-adjusted life-year analyses Outcome-based reimbursement or staged payment models Legitimate value of immunotherapy as shown by real-world evidence and longer follow-ups |
Bispecific Antibodies | CAR T Cell | |
---|---|---|
Production | “Off-the-shelf”: No need for manufacturing time, allowing for immediate treatment of the patient | Individual manufacturing for each patient, starting with autologous lymphapheresis Approach: Allogeneic CAR T cells under development |
Administration | Continuous intravenous infusion Approach: extended half-life bispecific antibodies | Punctual infusion of the product (dose is sometimes split up into several days to reduce AEs) |
T cell phenotype and effector function | Binding of endogenous CD8+ and CD4+ T cells, which have a superior cytotoxic function than naïve T cells | The product is mostly composed of naïve CD8+ and CD4+ T cells; these cells have higher self-renewal, survival, and penetration in lymphoid tissues |
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Rodríguez-Lobato, L.G.; Oliver-Caldés, A.; Moreno, D.F.; Fernández de Larrea, C.; Bladé, J. Why Immunotherapy Fails in Multiple Myeloma. Hemato 2021, 2, 1-42. https://doi.org/10.3390/hemato2010001
Rodríguez-Lobato LG, Oliver-Caldés A, Moreno DF, Fernández de Larrea C, Bladé J. Why Immunotherapy Fails in Multiple Myeloma. Hemato. 2021; 2(1):1-42. https://doi.org/10.3390/hemato2010001
Chicago/Turabian StyleRodríguez-Lobato, Luis Gerardo, Aina Oliver-Caldés, David F. Moreno, Carlos Fernández de Larrea, and Joan Bladé. 2021. "Why Immunotherapy Fails in Multiple Myeloma" Hemato 2, no. 1: 1-42. https://doi.org/10.3390/hemato2010001