Abstract
Multiple myeloma (MM) is a common hematologic malignancy characterized by clonal plasma cell proliferation. Despite significant therapeutic advancements with proteasome inhibitors, immunomodulatory drugs, and anti-B-cell maturation antigen (BCMA) therapies, the disease remains largely incurable. Immunoparesis, a severe state of immune dysfunction, exhibits high prevalence in MM patients and profoundly impacts prognosis. This review summarizes the pathogenic mechanisms and clinical characteristics of immunoparalysis, with a focus on its impact on prognosis and early-onset infections, the effects of contemporary drug therapies on immunoparalysis, and immune reconstitution.
1 Introduction
Multiple myeloma (MM) is the second most common hematologic malignancy, accounting for 10% of hematologic cancers (, ), with a median diagnosis age of 65 years (). This disease predominantly affects older adults and is characterized by malignant plasma cells that typically secrete monoclonal immunoglobulin, leading to end-organ damage, including anemia, renal impairment, osteolytic lesions, and hypercalcemia. Autologous stem cell transplantation (ASCT) remains the frontline treatment for MM. Meanwhile, the advent of novel agents and advancements in immunotherapy, particularly T-cell redirecting immunotherapies such as bispecific antibodies and chimeric antigen receptor (CAR) T-cell therapies, have significantly improved survival outcomes (). Nevertheless, MM remains largely incurable, with infections still contributing significantly to early mortality ().
Immunoparesis, the suppression of one or more uninvolved immunoglobulins (i.e., polyclonal immunoglobulins) in MM patients, such as the reduction of IgA and/or IgM levels in IgG MM patient, is a hallmark of MM and its precursor states, monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) (, ).It occurs in 80%–95% of MM patients (, ) and correlates with poorer treatment outcomes, including reduced response depth and survival. Notably, immunoparesis is not limited to a decrease in immunoglobulin levels but can also involve multiple immunoglobulin isotypes. Reconstitution of polyclonal immunoglobulins serves as a dynamic marker for assessing treatment efficacy and long-term outcomes (, ). Furthermore, immunoparesis significantly increases the risk of infections in MM patients, complicating their clinical management. This review discusses the pathogenesis of immunoparesis, its clinical features, its associations with cytogenetic abnormalities, and its prognostic implications. Additionally, we examine the impact of immunoparesis on infection risk, its recovery and reconstruction, and the effects of modern therapeutic regimens on immunoparesis. Lastly, we propose future research directions to enhance the understanding of immunoparesis in the context of MM.
Relevant studies were identified by searching PubMed and Web of Science (2000–2024) using keywords such as “immunoparesis”, “multiple myeloma”, “immune reconstitution”, “immunoglobulin suppression” and “immune recovery”.
2 Pathogenesis and cytogenetic interplay of immunoparesis in multiple myeloma
2.1 Mechanisms of immunoparesis
The pathogenesis of MM is complex, involving genetic mutations (, ), chromosomal translocations (–), aberrant signaling pathways (, ), and a supportive bone marrow microenvironment (, , ). Key oncogenic events include IgH translocations, such as t(11;14) and t(4;14), as well as chromosomal abnormalities like 1q gain and 13q deletion. These alterations promote cell cycle dysregulation and clonal expansion. In addition, disease progression is also influenced by interactions between myeloma cells and the bone marrow microenvironment. These interactions stimulate the secretion of cytokines and inflammatory mediators, including interleukin-6 (IL-6), insulin-like growth factor-1 (IGF-1), B-cell activating factor (BAFF), a proliferation-inducing ligand (APRIL), tumor necrosis factor-α (TNF-α), and vascular endothelial growth factor (VEGF). These soluble factors activate multiple signaling pathways, including NF-κB, JAK/STAT, MAPK, and PI3K/Akt/mTOR, which promote myeloma cell proliferation, survival, migration, and resistance to therapy (, , ).
Recent studies suggest that immunoparesis in MM may be closely related to interactions between anti-B-cell maturation antigen (BCMA) and its ligands, BAFF and APRIL (, ).BCMA, a transmembrane glycoprotein belonging to the tumor necrosis factor (TNF) receptor superfamily, is highly expressed on both normal and malignant plasma cells and serves as a hallmark surface antigen (). Upon binding with BAFF or APRIL, BCMA promotes plasma cell survival, proliferation, and polyclonal immunoglobulin secretion (–). However, membrane-bound BCMA can be cleaved by γ-secretase(GS), a multi-subunit protease complex, to generate soluble BCMA (sBCMA), which is released into the peripheral blood (, ). sBCMA competitively bind to BAFF and APRIL, thereby blocking their interaction with membrane-bound BCMA. This interference disrupts the plasma cell maturation and function, leading to impaired immunoglobulin synthesis and secretion, and ultimately contributing to immune dysfunction and the development of immunoparesis. The above mechanisms are shown in Figure 1 ().
Figure 1
2.2 Immunoparesis and cytogenetic abnormalities
Cytogenetic abnormalities are among the most common predictors of poor prognosis in MM (–). High-risk abnormalities, such as t(4;14), t(14;16), t(14;20), ≥3 copies of the 1q21 chromosomal band (1q21+), deletions of the 1p chromosomal arm (del(1p)), and deletions of the 17p13 chromosomal band (del(17p)) (), are strongly associated with disease progression. Evidence suggests that in newly diagnosed MM patients, primary cytogenetic abnormalities intensify the severity of immunoparesis. Specifically, patients with high-risk alterations, including t(4;14), t(14;16), or t(14;20), had a significantly higher proportion of polyclonal immunoglobulins suppressed below the normal range. Mechanistically, these cytogenetic abnormalities alter the bone marrow microenvironment, remodel the plasma cell niche, and suppress normal plasma cell function, ultimately reduce immunoglobulin production ().But to date, no more comparable studies have been reported in this field.
3 Incidence and clinical features of immunoparesis
Immunoparesis is more prevalent in MM patients aged >65 years (), with a reported incidence of 85%–90% in newly diagnosed cases (, ). The incidence further increases to 90%–95% in relapsed/refractory MM (RRMM) (), likely due to enhanced immune dysfunction caused by tumor resistance and immune escape. The prevalence of immunoparesis correlates with disease progression; early-stage MM exhibits a lower incidence (50%–60%), whereas advanced-stage MM demonstrates rates exceeding 90%. Specifically, among active MM cases, immunoparesis prevalence rises from 63% in Durie-Salmon (D-S) stage I to 90% in stage III (). A Greek study reported immunoparesis rates of 77%, 88%, and 94% in International Staging System (ISS) stages 1, 2, and 3, respectively ().
Moreover, immunoparesis is significantly associated with laboratory abnormalities, including decreased hemoglobin levels, reduced platelet counts, lower M-protein levels, and increased infiltration of bone marrow plasma cells(BMPC) (, ). While it occurs across all M-protein subtypes, studies offer conflicting conclusions regarding which subtype is most closely associated. A small retrospective study (n = 49) found that patients with IgG-type MM had significantly lower levels of polyclonal immunoglobulins compared to those with IgA or IgM types, suggesting stronger isotype-specific immunosuppression in the IgG subtype (). This study utilized serum electrophoresis, which is limited in differentiating monoclonal from polyclonal immunoglobulins. In contrast, a larger prospective cohort study (n = 1,755) using nephelometry reported a higher incidence of immunoparesis in patients with IgA-type MM than those with IgG-type (). This association remained significant after multivariate regression analysis. We speculate that differences in cohort size and testing methodology account for the discrepancies between the two studies.
Emerging evidence suggests that immunoparesis is not only a clinical feature of MGUS and SMM but may also drive disease progression. In MGUS patients, suppression of two or more uninvolved immunoglobulins significantly increased the risk of progression to MM (OR = 19.1), with prognostic value comparable to the IgA subtype, elevated M-protein, and abnormal free light chain ratios (). Moreover, the combination of immunoparesis and an abnormal bone marrow plasma cell phenotype helps identify high-risk MGUS patients, with a 5-year progression risk of up to 46% (). In SMM, deeper immunoglobulin suppression has similarly been linked to faster progression (). Specifically, patients with suppression of two immunoglobulin types experienced a median time to progression of only 32 months, compared to 159 months in those without suppression. Additionally, some researchers incorporated immunoparesis into their high-risk SMM evaluation model, reflecting its association with increased tumor burden ().
4 Prognostic and infection-related consequences of immunoparalysis in multiple myeloma
4.1 Impact on prognosis
Despite significant advancements in therapeutic strategies for MM, the disease remains largely incurable, with a 10-year survival rate of merely 17% (, ). This underscores the pressing need for a more nuanced understanding of prognostic factors and the establishment of reliable risk stratification systems to better identify high-risk patients, guide treatment intensification, and improve prognostic accuracy. To date, several prognostic systems, including the International Staging System (ISS) () and its revised version, the Revised International Staging System (R-ISS) (), have been established. The R-ISS integrates key factors such as β2-microglobulin, lactate dehydrogenase (LDH), and high-risk cytogenetic abnormalities. More recently, the introduction of sensitive markers like minimal residual disease (MRD) detection has improved clinical practice (, ). Research consistently shows that immunoparesis is significantly associated with inferior survival in MM patients, with greater severity correlating with worse outcomes (, ).These findings suggest that immunoparesis may serve as a valuable predictive biomarker for MM prognosis. Table 1 offers a comprehensive summary of the effects of immunoparesis on the prognosis of MM patients.
Table 1
| Study (author, year) | Cohort (n) | OS | PFS | Reference | ||
|---|---|---|---|---|---|---|
| With immunoparesis | No immunoparesis | With immunoparesis | No immunoparesis | |||
| Kastritis,et al., 2014 | 1755 | 41.5months | 55months | 25months | 60months | () |
| Chakraborty,et al., 2020 | 258 | 3‐year OS 40%-42% | 3‐year OS 60% | 2‐year PFS 20%-25% | 2‐year PFS 36% | () |
| Gao,et al., 2019 | 108 | estimated OS of not reach | 61months | 32months | 55months | () |
| Geng,et al., 2021 | 287 | 45.6months | 30.9months | 27.6months | 25.6months | () |
| González-Calle,et al., 2017 | 169 | 7.3years | 11.3years | 27.9 months | 60.4months | () |
Studies investigating the prognostic impact of immunoparalysis in patients with multiple myeloma.
4.1.1 For newly diagnosed multiple myeloma patients
At diagnosis, patients with immunoparesis typically experience worse overall survival (OS) and progression-free survival (PFS) compared to those without it (). In a cohort of 1,755 newly diagnosed multiple myeloma (NDMM) patients, reported preserved uninvolved immunoglobulins correlated with longer median OS compared to those with suppressed levels (55 vs. 41.5 months, P < 0.001), and immunoparesis remained an independent prognostic factor in multivariate analysis (HR = 0.781, P = 0.039) (). Geng et al. classified immunoparesis as deep (any uninvolved immunoglobulin <50% of the lower normal limit) or partial (≥2 suppressed isotypes), both of which were linked to significantly worse OS and PFS even after propensity score matching (). However, the study was limited by its single-center, retrospective design and relatively small sample size. Although propensity matching helped control confounding factors, selection bias could not be fully excluded. Additionally, a larger retrospective study analyzed 2,558 NDMM patients by stratifying them into three groups based on the degree of polyclonal IgM suppression. Median PFS decreased with increasing IgM suppression—1.97, 1.79, and 1.71 years across the least, intermediate, and most suppressed groups, respectively (P < 0.001). No similar trend was observed for IgG or IgA (). These findings suggest that IgM may serve as a more sensitive prognostic marker, though this could also relate to its lower baseline concentration and greater susceptibility to decline.
4.1.2 For relapsed multiple myeloma
In relapsed MM, immunoparesis remains associated with adverse outcomes, particularly at first relapse where it often coincides with higher tumor burden and shorter remission durations (, ). A study of 258 patients with first relapse stratified immunoparesis both qualitatively and quantitatively (). Qualitatively, patients were categorized into three groups: no immunoparesis (no suppression of uninvolved immunoglobulins), partial immunoparesis (suppression of at least one but not all), and complete immunoparesis (suppression of all uninvolved immunoglobulins). Although OS did not differ significantly among groups, 2-year PFS declined progressively (36%, 25%, and 20%), suggesting a strong link between the extent of immunoparesis and disease progression. Quantitative analysis used the average relative difference (ARD) between polyclonal immunoglobulin levels and the lower limit of normal, categorizing patients into no immunoparesis (ARD ≥ 0%), mild immunoparesis (ARD 0%−50%), and deep immunoparesis (ARD ≤−50%). Patients with deep immunoparesis had significantly worse OS and PFS compared to those with mild or no suppression. Interestingly, only IgM suppression showed a statistically significant association with prognosis, consistent with findings in newly diagnosed cohorts. This supports the hypothesis that IgM may be a more sensitive indicator of impaired immune surveillance.
In summary, immunoparesis is associated with poor outcomes in both newly diagnosed and relapsed MM, with IgM suppression showing consistent prognostic relevance across studies. However, most supporting data are retrospective and affected by heterogeneity in patient populations, definitions, treatment regimens, transplant status, and maintenance therapy, which may contribute to inconsistent results. Although multivariate analyses (e.g., HR = 0.781, P = 0.039) support its independent prognostic value, immunoglobulin suppression as a standalone marker has limitations and may be influenced by disease burden and treatment response. Future research should aim to standardize grading criteria and assess its additive value within multifactorial models.
4.2 Impact on infections
Infections are frequent and serious complications in MM, accounting for a substantial proportion of early morbidity and mortality (–). Approximately 45% of deaths within the first six months following diagnosis are attributed to infections (, ), with the highest risk occurring during the initial post-diagnosis period and treatment for relapsed or refractory disease (, , ). Modern therapies, including proteasome inhibitors, immunomodulatory drugs, and monoclonal antibodies, may further weaken host immune defenses, thereby increasing infection risk. Consequently, infection prevention and management are critical in MM treatment.
Immunoparesis, which impairs humoral immunity, increases susceptibility to infections (). A recent retrospective study involving 430 newly diagnosed patients reported that 59.5% experienced ≥Grade 3 infections within the first three months. Respiratory infections predominated, and bacterial infections constituted the majority of identified cases, findings consistent with observations from comparable studies (). Patients with immunoparesis exhibited significantly higher early infection rates compared to those without immunoglobulin suppression. Based on these findings, a predictive model incorporating immunoparesis was developed to assess early infection risk in MM, suggesting that immunoparesis may negatively impact prognosis by increasing susceptibility to infections. In contrast, other studies argue that the adverse prognostic impact of immunoparesis cannot be primarily explained by elevated infection rates (). Thus, the role of immunoparesis in mediating poor outcomes through infection remains inconclusive and warrants further investigation.
5 Recovery and reconstitution of immunoparesis
Immunoparesis is recognized as a poor prognostic indicator in MM, prompting researchers to explore whether reversing this condition during treatment can lead to clinical benefits. Several studies have examined the restoration of polyclonal immunoglobulins in various therapeutic contexts (, , ). In particular, patients undergoing ASCT often show a gradual recovery of immunoglobulin levels within the first year (). This increase may reflect the reconstitution of the immune system and could be linked to improved long-term outcomes.
Analysis of a 295-patient ASCT cohort revealed that individuals achieving immunoglobulin recovery within one year had significantly improved PFS (60.4 vs. 27.9 months) and OS (11.3 vs. 7.3 years) compared to those without recovery (). Earlier recovery was linked to better outcomes, with median PFS of 69.3, 52.9, and 27.9 months for patients recovering within 6 months, between 6–12 months, and those who did not recover within one year, respectively (P < 0.001). Additionally, a higher proportion of normal plasma cells (nPCs) in bone marrow at day 100 post- ASCT was associated with immunoglobulin recovery, suggesting that early nPC reconstitution may serve as a predictive marker for subsequent immune restoration, consistent with observations reported in other studies ().
Recovery patterns have also been noted in patients undergoing allogeneic stem cell transplantation (alloSCT) and found that a majority experienced gradual recovery of polyclonal immunoglobulins within one year, particularly those with non-relapsing patients (). These findings highlight the potential clinical relevance of immune reconstitution after alloSCT. Nonetheless, due to the small sample size and lack of multivariate analysis, the conclusions remain exploratory.
In newly diagnosed MM patients not undergoing transplantation, polyclonal immunoglobulin recovery during therapy has similarly been linked to improved survival (). Even after adjusting for known prognostic variables such as ISS stage, LDH, response depth, and treatment regimen, this association remained statistically significant, underscoring the independent prognostic value of immune reconstitution.
Overall, immunoglobulin recovery correlates with improved survival in MM patients, but the variability across studies, patient populations, and treatment regimens calls for further research. Future studies should standardize definitions of immunoglobulin recovery and integrate it with other prognostic factors such as MRD and immune phenotyping to clarify its role in multifactorial prognostic models.
6 Impact of modern therapeutic regimens on immunoparesis
Current frontline pharmacologic treatment strategies for MM primarily rely on combination regimens that include proteasome inhibitors (e.g., bortezomib, V), immunomodulatory agents (e.g., lenalidomide, R), corticosteroids, and monoclonal antibodies (e.g., daratumumab, D) (, ). These therapies have significantly improved response depth and patient survival, and their effects on immune function are gaining increasing attention. Recent studies have demonstrated that induction regimens based on V and R, such as RD, VD, and VRD, not only effectively reduce tumor burden but also promote the recovery of uninvolved immunoglobulins, suggesting a potential role in alleviating immunoparesis (). This effect may be attributed to the ability of R and V to inhibit the BAFF/APRIL/BCMA signaling axis ().
In parallel, therapeutic strategies targeting soluble B-cell maturation antigen (sBCMA) present novel opportunities for mitigating immune dysfunction. Preclinical animal studies have shown that small-molecule γ-secretase inhibitors (GSIs) can block BCMA shedding, enhance its membrane-bound expression, and reduce circulating sBCMA levels, thereby improving CAR-T cell recognition and cytotoxicity against MM cells (). However, whether GSIs can independently alleviate immunoparesis by reducing sBCMA production or enhance long-term prognosis, remains to be determined. Future studies should explore the immunomodulatory effects of GSIs outside of CAR-T therapeutic contexts, particularly their ability to restore uninvolved immunoglobulin production and reverse immunoparesis.
7 Summary and perspectives
Immunoparesis, defined by suppression of uninvolved polyclonal immunoglobulins, is common in MM. It is strongly associated with inferior prognosis and increased infection risk. Evidence shows that early recovery of uninvolved immunoglobulins, particularly within one year post-ASCT, correlates with improved PFS and OS. Therefore, dynamic monitoring of immunoglobulin levels during treatment may serve as an important tool for assessing immune reconstitution and long-term treatment response.
Future efforts should aim to incorporate immunoparesis into established prognostic models such as ISS, R-ISS, MRD status, and immune phenotyping. This could help develop composite scoring systems that combine clinical and immune-related factors. We recommend establishing a standardized stratification framework for immunoparesis based on both qualitative and quantitative criteria to improve cross-study comparability and clarify its prognostic relevance. Immunoparesis may serve as a surrogate marker for immune competence. Future studies could use it to stratify patients and predict immune responses in vaccine trials, infection risk assessment, and CAR-T eligibility. Future prospective trials should consider using immunoglobulin recovery as a clinical endpoint to assess the immune effects of therapies such as IMiDs, monoclonal antibodies, or cellular therapies. Clinical studies could also integrate biomarkers based on immunoglobulin recovery into treatment decision-making and further investigate immunoparesis as a potential therapeutic target.
Statements
Author contributions
HW: Writing – original draft, Writing – review & editing. JC: Writing – original draft, Writing – review & editing.
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References
1
PalumboAAndersonK. Multiple myeloma. N Engl J Med. (2011) 364:1046–60. doi: 10.1056/NEJMra1011442
2
KyleRARajkumarSV. Multiple myeloma. Blood. (2008) 111:2962–72. doi: 10.1182/blood-2007-10-078022
3
KyleRAGertzMAWitzigTELustJALacyMQDispenzieriAet al. Review of 1027 patients with newly diagnosed multiple myeloma. Mayo Clin Proc. (2003) 78:21–33. doi: 10.4065/78.1.21
4
MalardFNeriPBahlisNJTerposEMoukalledNHungriaVTMet al. Multiple myeloma. Nat Rev Dis Primers. (2024) 10:1–21. doi: 10.1038/s41572-024-00529-7
5
MinnieSAHillGR. Immunotherapy of multiple myeloma. J Clin Invest. (2005) 130:1565–75. doi: 10.1172/JCI129205
6
PruzanskiWGidonMSRoyA. Suppression of polyclonal immunoglobulins in multiple myeloma: Relationship to the staging and other manifestations at diagnosis. Clin Immunol Immunopathology. (1980) 17:280–6. doi: 10.1016/0090-1229(80)90097-5
7
ChakrabortyRRybickiLNakashimaMODeanRMFaimanBMSamarasCJet al. Characterisation and prognostic impact of immunoparesis in relapsed multiple myeloma. Br J Haematol. (2020) 189:1074–82. doi: 10.1111/bjh.16488
8
ChahinMBranhamZFoxALeurindaCLeurindaCKeruakousAR. Clinical considerations for immunoparesis in multiple myeloma. Cancers (Basel). (2022) 14:2278. doi: 10.3390/cancers14092278
9
KastritisEZagouriFSymeonidisARoussouMSioniAPouliAet al. Preserved levels of uninvolved immunoglobulins are independently associated with favorable outcome in patients with symptomatic multiple myeloma. Leukemia. (2014) 28:2075–9. doi: 10.1038/leu.2014.110
10
HarutyunyanNMVardanyanSGhermeziMGottliebJBerensonAAndreu-VieyraCet al. Levels of uninvolved immunoglobulins predict clinical status and progression-free survival for multiple myeloma patients. Br J Haematol. (2016) 174:81–7. doi: 10.1111/bjh.14026
11
González-CalleVCerdáSLabradorJSobejanoEGonzález-MenaBAguileraCet al. Recovery of polyclonal immunoglobulins one year after autologous stem cell transplantation as a long-term predictor marker of progression and survival in multiple myeloma. Haematologica. (2017) 102:922–31. doi: 10.3324/haematol.2016.158345
12
NeuseCJLomasOCSchliemannCShenYJManierSBustorosMet al. Genome instability in multiple myeloma. Leukemia. (2020) 34:2887–97. doi: 10.1038/s41375-020-0921-y
13
DadzieTGGreenAC. The role of the bone microenvironment in regulating myeloma residual disease and treatment. Front Oncol. (2022) 12:999939. doi: 10.3389/fonc.2022.999939
14
GuCWangWTangXXuTZhangYGuoMet al. CHEK1 and circCHEK1_246aa evoke chromosomal instability and induce bone lesion formation in multiple myeloma. Mol Cancer. (2021) 20:84. doi: 10.1186/s12943-021-01380-0
15
TangXGuoMDingPDengZKeMYuanYet al. BUB1B and circBUB1B_544aa aggravate multiple myeloma Malignancy through evoking chromosomal instability. Signal Transduct Target Ther. (2021) 6:361. doi: 10.1038/s41392-021-00746-6
16
LuoSSuTZhouXHuW-XHuJ. Chromosome 1 instability in multiple myeloma: Aberrant gene expression, pathogenesis, and potential therapeutic target. FASEB J. (2022) 36:e22341. doi: 10.1096/fj.202200354
17
HuJHuW-X. Targeting signaling pathways in multiple myeloma: Pathogenesis and implication for treatments. Cancer Lett. (2018) 414:214–21. doi: 10.1016/j.canlet.2017.11.020
18
JungYYUmJ-YNasifOAlharbiSASethiGAhnKS. Blockage of the JAK/STAT3 signaling pathway in multiple myeloma by leelamine. Phytomedicine. (2021) 87:153574. doi: 10.1016/j.phymed.2021.153574
19
YangPQuYWangMChuBChenWZhengYet al. Pathogenesis and treatment of multiple myeloma. MedComm (2020). (2022) 3:e146. doi: 10.1002/mco2.146
20
LopesRCaetanoJBarahonaFPestanaCFerreiraBVLourençoDet al. Multiple myeloma-derived extracellular vesicles modulate the bone marrow immune microenvironment. Front Immunol. (2022) 13:909880. doi: 10.3389/fimmu.2022.909880
21
LuQYangDLiHNiuTTongA. Multiple myeloma: signaling pathways and targeted therapy. Mol BioMed. (2024) 5:25. doi: 10.1186/s43556-024-00188-w
22
PengYLiFZhangPWangXShenYFengYet al. IGF-1 promotes multiple myeloma progression through PI3K/Akt-mediated epithelial-mesenchymal transition. Life Sci. (2020) 249:117503. doi: 10.1016/j.lfs.2020.117503
23
SanchezEGillespieATangGFerrosMHarutyunyanNMVardanyanSet al. Soluble B-cell maturation antigen mediates tumor-induced immune deficiency in multiple myeloma. Clin Cancer Res. (2016) 22:3383–97. doi: 10.1158/1078-0432.CCR-15-2224
24
RaviPKumarSGonsalvesWBuadiFLacyMQGoRSet al. Changes in uninvolved immunoglobulins during induction therapy for newly diagnosed multiple myeloma. Blood Cancer J. (2017) 7:e569. doi: 10.1038/bcj.2017.46
25
MoorePABelvedereOOrrAPieriKLaFleurDWFengPet al. BLyS: member of the tumor necrosis factor family and B lymphocyte stimulator. Science. (1999) 285:260–3. doi: 10.1126/science.285.5425.260
26
TaiY-TAcharyaCAnGMoschettaMZhongMYFengXet al. APRIL and BCMA promote human multiple myeloma growth and immunosuppression in the bone marrow microenvironment. Blood. (2016) 127:3225–36. doi: 10.1182/blood-2016-01-691162
27
RennertPSchneiderPCacheroTGThompsonJTrabachLHertigSet al. A soluble form of B cell maturation antigen, a receptor for the tumor necrosis factor family member APRIL, inhibits tumor cell growth. J Exp Med. (2000) 192:1677–84. doi: 10.1084/jem.192.11.1677
28
ThompsonJSSchneiderPKalledSLWangLLefevreEACacheroTGet al. Baff binds to the tumor necrosis factor receptor–like molecule B cell maturation antigen and is important for maintaining the peripheral B cell population. J Exp Med. (2000) 192:129–36. doi: 10.1084/jem.192.1.129
29
ChenYChenZCaoJLinLLiJ. γ-Secretase inhibition increases efficacy of BCMA-specific chimeric antigen receptor T cells in multiple myeloma. Hematology. (2024) 29:2329378. doi: 10.1080/16078454.2024.2329378
30
JiangSLiHZhangLMuWZhangYChenTet al. Generic Diagramming Platform (GDP): a comprehensive database of high-quality biomedical graphics. Nucleic Acids Res. (2025) 53:D1670–6. doi: 10.1093/nar/gkae973
31
BoydKDRossFMChiecchioLDagradaGKonnZJTapperWJet al. A novel prognostic model in myeloma based on co-segregating adverse FISH lesions and the ISS: analysis of patients treated in the MRC Myeloma IX trial. Leukemia. (2012) 26:349–55. doi: 10.1038/leu.2011.204
32
FonsecaRBloodERueMHarringtonDOkenMMKyleRAet al. Clinical and biologic implications of recurrent genomic aberrations in myeloma. Blood. (2003) 101:4569–75. doi: 10.1182/blood-2002-10-3017
33
KeatsJJReimanTMaxwellCATaylorBJLarrattLMMantMJet al. In multiple myeloma, t(4;14)(p16;q32) is an adverse prognostic factor irrespective of FGFR3 expression. Blood. (2003) 101:1520–9. doi: 10.1182/blood-2002-06-1675
34
ChangHQiCYiQ-LReeceDStewartAK. p53 gene deletion detected by fluorescence in situ hybridization is an adverse prognostic factor for patients with multiple myeloma following autologous stem cell transplantation. Blood. (2005) 105:358–60. doi: 10.1182/blood-2004-04-1363
35
SonneveldPAvet-LoiseauHLonialSUsmaniSSiegelDAndersonKCet al. Treatment of multiple myeloma with high-risk cytogenetics: a consensus of the International Myeloma Working Group. Blood. (2016) 127:2955–62. doi: 10.1182/blood-2016-01-631200
36
CaroJCairnsDMenziesTBoyleEPawlynCCookGet al. Impact of etiological cytogenetic abnormalities on the depth of immunoparesis and survival in newly diagnosed multiple myeloma. Clin Lymphoma Myeloma Leukemia. (2022) 22:e279–84. doi: 10.1016/j.clml.2021.10.008
37
CherryBMCostelloRZingoneABurrisJKordeNManasanchEet al. Immunoparesis and monoclonal gammopathy of undetermined significance are disassociated in advanced age. Am J Hematol. (2013) 88:89–92. doi: 10.1002/ajh.23355
38
HeaneyJLJCampbellJPIqbalGCairnsDRichterAChildJAet al. Characterisation of immunoparesis in newly diagnosed myeloma and its impact on progression-free and overall survival in both old and recent myeloma trials. Leukemia. (2018) 32:1727–38. doi: 10.1038/s41375-018-0163-4
39
ZhangMChengQZhaoFXuALiQHuYet al. Development of a nomogram prognostic model for early Grade ≥ 3 infection in newly diagnosed multiple myeloma based on immunoparesis. Int Immunopharmacol. (2024) 126:111277. doi: 10.1016/j.intimp.2023.111277
40
WangLYoungDC. Suppression of polyclonal immunoglobulin production by M-proteins shows isotype specificity. Ann Clin Lab Sci. (2001) 31:274–8.
41
LandgrenOHofmannJNMcShaneCMSantoLHultcrantzMKordeNet al. Association of immune marker changes with progression of monoclonal gammopathy of undetermined significance to multiple myeloma. JAMA Oncol. (2019) 5:1293–301. doi: 10.1001/jamaoncol.2019.1568
42
Pérez-PersonaEVidrialesM-BMateoGGarcía-SanzRMateosM-Vde CocaAGet al. New criteria to identify risk of progression in monoclonal gammopathy of uncertain significance and smoldering multiple myeloma based on multiparameter flow cytometry analysis of bone marrow plasma cells. Blood. (2007) 110:2586–92. doi: 10.1182/blood-2007-05-088443
43
KyleRARemsteinEDTherneauTMDispenzieriAKurtinPJHodnefieldJMet al. Clinical course and prognosis of smoldering (asymptomatic) multiple myeloma. N Engl J Med. (2007) 356:2582–90. doi: 10.1056/NEJMoa070389
44
BladéJDimopoulosMRosiñolLRajkumarSVKyleRA. Smoldering (Asymptomatic) multiple myeloma: current diagnostic criteria, new predictors of outcome, and follow-up recommendations. J Clin Oncol. (2010) 28:690–7. doi: 10.1200/JCO.2009.22.2257
45
Wallington-BeddoeCTMynottRL. Prognostic and predictive biomarker developments in multiple myeloma. J Hematol Oncol. (2021) 14:151. doi: 10.1186/s13045-021-01162-7
46
KumarSKDispenzieriALacyMQGertzMABuadiFKPandeySet al. Continued improvement in survival in multiple myeloma: changes in early mortality and outcomes in older patients. Leukemia. (2014) 28:1122–8. doi: 10.1038/leu.2013.313
47
GreippPRSan MiguelJDurieBGMCrowleyJJBarlogieBBladéJet al. International staging system for multiple myeloma. J Clin Oncol. (2005) 23:3412–20. doi: 10.1200/JCO.2005.04.242
48
PalumboAAvet-LoiseauHOlivaSLokhorstHMGoldschmidtHRosinolLet al. Revised international staging system for multiple myeloma: A report from international myeloma working group. J Clin Oncol. (2015) 33:2863–9. doi: 10.1200/JCO.2015.61.2267
49
SzalatREAndersonKCMunshiNC. Role of minimal residual disease assessment in multiple myeloma. Haematologica. (2024) 109:2049–59. doi: 10.3324/haematol.2023.284662
50
GengCYangGWangHWuYLengYZhouHet al. Deep and partial immunoparesis is a poor prognostic factor for newly diagnosed multiple myeloma patients. Leuk Lymphoma. (2021) 62:883–90. doi: 10.1080/10428194.2020.1855345
51
GaoWLiJWuYLiYLengYLiuAet al. Immunoparesis recovery 1 year after ASCT is independently associated with favorable survival in patients with symptomatic multiple myeloma who undergo autologous stem cell transplantation. Ann Hematol. (2019) 98:1177–84. doi: 10.1007/s00277-018-3574-4
52
SørrigRKlausenTWSalomoMVangstedAJFrølundUCAndersenKTet al. Immunoparesis in newly diagnosed Multiple Myeloma patients: Effects on overall survival and progression free survival in the Danish population. PloS One. (2017) 12:e0188988. doi: 10.1371/journal.pone.0188988
53
PozziSBariAPecherstorferMValletS. Management of adverse events and supportive therapy in relapsed/refractory multiple myeloma. Cancers (Basel). (2021) 13:4978. doi: 10.3390/cancers13194978
54
BlimarkCHolmbergEMellqvistU-HLandgrenOBjörkholmMHultcrantzMet al. Multiple myeloma and infections: a population-based study on 9253 multiple myeloma patients. Haematologica. (2015) 100:107–13. doi: 10.3324/haematol.2014.107714
55
HolmströmMOGimsingPAbildgaardNAndersenNFHellebergCClausenNATet al. Causes of early death in multiple myeloma patients who are ineligible for high-dose therapy with hematopoietic stem cell support: A study based on the nationwide Danish Myeloma Database. Am J Hematol.90:271–366. doi: 10.1002/ajh.23932
56
de la RubiaJCejalvoMJRibasP. Infectious complications in patients with newly diagnosed multiple myeloma: A complication from the past? Leuk Lymphoma. (2016) 57:258–68. doi: 10.3109/10428194.2015.1088647
57
DumontetCHulinCDimopoulosMABelchADispenzieriALudwigHet al. A predictive model for risk of early grade ≥ 3 infection in patients with multiple myeloma not eligible for transplant: analysis of the FIRST trial. Leukemia. (2018) 32:1404–13. doi: 10.1038/s41375-018-0133-x
58
AugustsonBMBegumGDunnJABarthNJDaviesFMorganGet al. Early mortality after diagnosis of multiple myeloma: analysis of patients entered onto the United kingdom Medical Research Council trials between 1980 and 2002–Medical Research Council Adult Leukaemia Working Party. J Clin Oncol. (2005) 23:9219–26. doi: 10.1200/JCO.2005.03.2086
59
SavageDGLindenbaumJGarrettTJ. Biphasic pattern of bacterial infection in multiple myeloma. Ann Intern Med. (1982) 96:47–50. doi: 10.7326/0003-4819-96-1-47
60
TwomeyJJ. Infections complicating multiple myeloma and chronic lymphocytic leukemia. Arch Intern Med. (1973) 132:562–5. doi: 10.1001/archinte.1973.03650100076014
61
PrattGGoodyearOMossP. Immunodeficiency and immunotherapy in multiple myeloma. Br J Haematology. (2007) 138:563–79. doi: 10.1111/j.1365-2141.2007.06705.x
62
SørrigRKlausenTWSalomoMVangstedAGimsingP. Risk factors for infections in newly diagnosed Multiple Myeloma patients: A Danish retrospective nationwide cohort study. Eur J Haematol. (2019) 102:182–90. doi: 10.1111/ejh.13190
63
PorrataLFGertzMAInwardsDJLitzowMRLacyMQTefferiAet al. Early lymphocyte recovery predicts superior survival after autologous hematopoietic stem cell transplantation in multiple myeloma or non-Hodgkin lymphoma. Blood. (2001) 98:579–85. doi: 10.1182/blood.V98.3.579
64
EisfeldCEßelingEWullenkordRKhandanpourCReuschJMikeschJ-Het al. Long-term survival and polyclonal immunoglobulin reconstitution after allogeneic stem cell transplantation in multiple myeloma. Ann Hematol. (2020) 99:1907–15. doi: 10.1007/s00277-020-04068-5
65
DávilaJGonzález-CalleVEscalanteFCerdáSPuigNGarcía-SanzRet al. Recovery of polyclonal immunoglobulins during treatment in patients ineligible for autologous stem-cell transplantation is a prognostic marker of longer progression-free survival and overall survival. Br J Haematol. (2022) 198:278–87. doi: 10.1111/bjh.18182
66
CowanAJGreenDJKwokMLeeSCoffeyDGHolmbergLAet al. Diagnosis and management of multiple myeloma: A review. JAMA. (2022) 327:464–77. doi: 10.1001/jama.2022.0003
67
QuachHRitchieDStewartANeesonPHarrisonSSmythMet al. Mechanism of action of immunomodulatory drugs (IMiDS) in multiple myeloma. Leukemia. (2010) 24:22–32. doi: 10.1038/leu.2009.236
68
ShenXGuoYQiJShiWWuXNiHet al. Study on the association between miRNA-202 expression and drug sensitivity in multiple myeloma cells. Pathol Oncol Res. (2016) 22:531–9. doi: 10.1007/s12253-015-0035-4
Summary
Keywords
multiple myeloma, immunoparesis, bone marrow microenvironment, prognosis, infections, immune reconstitution
Citation
Wang H and Chen J (2025) Immunoparesis in multiple myeloma: a current overview. Front. Oncol. 15:1628144. doi: 10.3389/fonc.2025.1628144
Received
13 May 2025
Accepted
08 September 2025
Published
23 September 2025
Volume
15 - 2025
Edited by
Liren Qian, Fifth Medical Center of the PLA General Hospital, China
Reviewed by
Anna Maria Corsale, University of Palermo, Italy
Ling Zhong, Sichuan Academy of Medical Sciences and Sichuan Provincial People’s Hospital, China
Linqin Wang, Zhejiang University, China
Updates
Copyright
© 2025 Wang and Chen.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Jianbin Chen, 201679@hospital.cqmu.edu.cn
Disclaimer
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