Your privacy, your choice

We use essential cookies to make sure the site can function. We also use optional cookies for advertising, personalisation of content, usage analysis, and social media.

By accepting optional cookies, you consent to the processing of your personal data - including transfers to third parties. Some third parties are outside of the European Economic Area, with varying standards of data protection.

See our privacy policy for more information on the use of your personal data.

for further information and to change your choices.
Skip to main content
Download PDF

Abnormal proportions and functions of myeloid-derived suppressor cells in peripheral blood of patients with diffuse large B-cell lymphoma

BMC Cancer volume 25, Article number: 771 (2025) Cite this article

Abstract

Background

Myeloid-derived suppressor cells (MDSCs) are a subset of immature myeloid cells with immunosuppressive properties. Evidence suggests that abnormal immune system can lead to immune dysfunction and increase the risk of developing diffuse large B-cell lymphoma (DLBCL). This study investigated the abnormality of MDSCs in the peripheral blood of patients with DLBCL.

Methods

Expression, apoptosis, and proliferation of MDSCs was measured in the peripheral blood DLBCL patients and healthy donors (HDs) via flow cytometer. The co-culture groups included the MDSCs and DLBCL cells line and MDSCs and T cells. Using flow cytometry detected MDSCs and T cells proliferation, apoptosis, T cells activation and function in the co-culture groups. RNA transcriptome sequencing analysis was conducted on DLBCL-MDSCs and HDs-MDSCs. Combined with the clinicopathological data of DLBCL patients, the correlation between MDSCs and DLBCL progression was analyzed.

Results

The expression of MDSCs in patients newly diagnosed with DLBCL was elevated. DLBCL tumor cells could stimulate MDSCs growth. DLBCL-MDSCs showed stronger immunosuppressive ability to T cells proliferation, activation and secretion of cytokines and associated with several clinical indicators such as Ann Arbor stage, serum LDH level, and lymphoma IPI score.

Conclusion

This study investigated the abnormality of MDSCs and underscored the critical role of MDSCs in suppressing T cell function in DLBCL patients. It provides certain laboratory evidence for MDSCs as biomarkers of disease progression and treatment response in DLBCL.

Peer Review reports

Introduction

Diffuse large B-cell lymphoma (DLBCL), the predominant subtype of non-Hodgkin lymphoma, is characterized by rapid growth and high invasiveness [1, 2]. Despite the efficacy of the R-CHOP regimen in prolonging the survival time of patients with DLBCL, approximately half the patients ultimately experience relapse or develop refractory disease after treatment [3,4,5]. Immunotherapy could improve the prognosis of DLBCL, and a better understanding of the impaired immune function of patients with DLBCL may provide a novel strategy for DLBCL immunotherapy [6,7,8].

Myeloid-derived suppressor cells (MDSCs) are a crucial type of immunosuppressive cell and are defined as CD45+HLA-DRlow/−CD11b+ CD33+ cells [9, 10]. MDSCs are rarely identified in the peripheral blood (PB) of healthy individuals but undergo considerable expansion during inflammation and infection, particularly after tumor onset [11, 12]. Subsequently, circulating MDSCs can migrate to the tumor site and exert potent immunosuppressive effects [13, 14]. For example, the amounts of MDSCs are elevated in breast cancer, metastatic pediatric sarcoma, and colorectal cancer [15,16,17]. It’s reported that elevated MDSCs levels are associated with decreased overall survival in patients with cervical cancer and melanoma [18,19,20].

MDSCs play an essential role in the pathogenesis and progression of different tumors and can inhibit T cells proliferation and function by secreting arginase-1, inducible nitric oxide synthase, nitric oxide, and reactive oxygen species [21,22,23]. Increased MDSCs can suppress T cells activity by modulating glycolysis, thereby promoting breast cancer progression [24]. Additionally, MDSCs can increase the risk of colon cancer by modulating interleukin-10 expression [25, 26]. MDSCs in the PB of individuals with multiple myeloma impede antigenic CD8+ T cells stimulation and hinder T cells functionality by influencing the cell cycle and reducing T cell receptor (TCR) expression on the surface of mature T cells [27]. Hence, elucidating the biological attributes and immunosuppressive capabilities of MDSCs may offer novel perspectives for clinical assessment and therapy.

Although the amounts of MDSCs increase in the peripheral blood in other subtypes of lymphoma such as Hodgkin lymphoma [28]. However, the immunopathological impact of MDSCs on patients with DLBCL requires more comprehensive exploration. The exploratory endpoint of this study aimed to assess the quantity and immunosuppressive capabilities of MDSCs in the PB of patients with DLBCL to elucidate their impact on the immune system in DLBCL.

Materials and methods

Human samples

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Review Committee of Fujian Medical University Union Hospital (2021WSJK018) with informed consent from all the patients. The primary exploratory endpoint of this study is to elucidate the proportion and functional abnormalities of MDSCs in the peripheral blood of newly diagnosed DLBCL patients. In this study, peripheral blood (PB) samples were collected from 65 newly diagnosed DLBCL patients and 79 healthy donors (HDs). Bone marrow (BM) samples were collected from 11 newly diagnosed DLBCL patients and 14 HD. These samples were derived from residual tubes previously stored in the hospital biobank. All human PB and BM samples were collected from DLBCL patients prior to treatment between August 2021 and July 2023. All patients met the DLBCL diagnostic criteria, which included the Ann Arbor stage, serum lactate dehydrogenase (LDH) level, B symptoms, and lymphoma International Prognostic Index (IPI) score. No patients had infectious, autoimmune, or other tumorous diseases.

Treatment

The treatment regimen primarily included the standard R-CHOP chemotherapy protocol (a combination therapy of rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone). In this study, all patients received standard R-CHOP chemotherapy, with 11 patients achieving complete remission (CR) after 6-course of chemotherapy and were evaluated the circulating MDSCs. Patients who did not respond to R-CHOP were excluded from in this study.

Surface staining

Antibody markers for flow cytometry are provided in Supplementary Table 1. PB and BM samples (100 µL) were collected and transferred into test tubes. Red blood cells were lysed using red blood cell lysis buffer (BD Biosciences, USA) for 15 min. The cells were washed and resuspended in phosphate-buffered saline. Fc receptor-blocking agent was added and the cells were incubated at room temperature for 15 min. Fixable Viability Stain working solution (1 µL; 1:1000) was added to each tube and incubated at room temperature for 15 min. The appropriate concentration of fluorescently labeled monoclonal antibodies was added for staining. The samples were then incubated for 30 min at 4 °C. The stained cells were washed and resuspended in phosphate-buffered saline. Data acquisition and analysis were performed using a FACSCelesta Flow Cytometer and analyzed with FlowJoV 10.8.1 software (BD Biosciences, USA).

Determination of MDSCs apoptosis and proliferation

MDSCs were collected for apoptotic staining (Annexin V/7AAD) according to the manufacturer’s instructions after surface staining with the CD45, HLA-DR, CD33, and CD11c antibodies. Intracellular staining was performed according to the manufacturer’s instructions to detect intracellular Ki67 (BD Biosciences, USA).

Co-culture system

The human DLBCL cell lines, DB and SU-DHL-6, were provided by the Cell Bank of the Chinese Academy of Sciences (Shanghai, China). After surface staining, MDSCs and CD3+ T cells were separated using FACS Aria III (BD Biosciences, USA). The co-culture groups included the MDSCs and DLBCL cells line and MDSCs and T cells groups. A Transwell insert (Millipore, USA) with a pore size of 0.4 μm was used to co-culture cells. The number of cells in the above group was 5.0 × 104 cells/well. The cells were cultured in RPMI-1640 medium (Gibco, USA) enriched with 10% fetal bovine serum (Gibco, USA) and incubated at 37 °C in a humidified atmosphere containing 5% CO2.

T cells proliferation, activation, and cytokine expression assay

T cells were stimulated for the proliferation assay using soluble anti-CD3/CD28 antibodies according to standard procedures (STEMCELL Technologies, Canada). T cells were stained with a panel of markers, including CD3, CD69, and CD25, for the activation assay. The cells were stained with Ki67 manufacturer’s instructions.

For cytokine detection, T cells were activated using Leukocyte Activation Cocktail with GolgiPlug (BD Biosciences, USA) at 37℃ in a 5% CO2 atmosphere for 6 h. The cells were stained with the appropriate concentration of granzyme B, interferon-gamma (IFN-γ), tumor necrosis factor-alpha (TNF-α), and interleukin-17 (IL-17) antibodies according to the manufacturer’s instructions. A multicolor FACSCelesta Flow Cytometer was used for all analyses.

RNA sequencing

MDSCs from patients with DLBCL and HDs were isolated using flow cytometry. Total RNA was extracted from cells using TRIzol reagent (Invitrogen, USA) following the manufacturer’s guidelines. RNA sequencing was conducted at Novogene (Beijing, China). Data analyses were performed on the NovoMagic platform (https://magic.novogene.com), which included constructing heatmaps, volcano plot analysis, Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and Gene Set Enrichment Analysis (GSEA).

Statistical analyses

Statistical analyses were performed using the SPSS (version 26.0; Chicago, USA). Under the premise of normal distribution and homogeneity of variance, an independent-sample t-test was used for comparison between the two groups, and the data are represented as the mean ± standard deviation (x̄ ± SD). For data with non-normal distribution, the Mann–Whitney U test was used between the two groups, and the median represents the data. To evaluate correlation, Pearson and Spearman correlation coefficient test were used. Statistical significance was set at p < 0.05.

Result

MDSCs expand aberrantly in patients with DLBCL

The molecular marker was defined as CD45+HLA-DR−CD33+CD11b+ for MDSCs. The flow cytometry gating strategy for MDSCs is detailed in Fig. 1A. The frequency of circulating MDSCs in patients with DLBCL (43.90%) was considerably elevated compared to that of HDs (23.80%; Fig. 1B). Interestingly, the proportion of MDSCs in the BM was consistent with the difference in the PB for patients with DLBCL (63.36%) and HDs (30.44%; Fig. 1C).

Fig. 1
figure 1

MDSCs expand aberrantly in patients with DLBCL. (A) Flow cytometry gating strategy for MDSCs: The molecular marker was defined as CD45+HLA-DR−CD33+CD11b+ for MDSCs. (B) Proportion of MDSCs in the peripheral blood of patients with DLBCL (n = 65) and healthy donors (HDs) (n = 79). (C) Proportion of MDSCs in the bone marrow of patients with DLBCL (n = 11) and HDs (n = 14)

Full size image

MDSCs in patients with DLBCL exhibit increased proliferation and decreased apoptosis

MDSCs proliferation and apoptosis in the PB of patients with DLBCL were assessed to explore the underlying factors contributing to MDSCs expansion in DLBCL. The Ki67 expression levels in MDSCs were elevated in patients with DLBCL (12.82%) compared to those of HDs (4.47%; Fig. 2A). MDSCs from patients with DLBCL displayed a decreased apoptosis ratio (45.50% vs. 61.09%; Fig. 2B). In addition, compared to independently cultured MDSCs (0.91%), the proliferation of MDSCs co-cultured with DLBCL cell lines increased (25.51% vs. 22.42%; Fig. 2C), whereas the apoptosis rate decreased (87.63% vs. 82.15% vs. 70.83%; Fig. 2D). These results imply that DLBCL cells actively contribute to increased MDSCs proliferation and decreased apoptosis.

Fig. 2
figure 2

MDSCs in patients with DLBCL exhibit increased proliferation and decreased apoptosis. (A-B) Quantification of the Ki67 expression levels and the apoptosis status in circulating MDSCs from patients with DLBCL (n = 17) and HDs (n = 8). (C-D) Quantification of the Ki67 expression levels and the apoptosis status in circulating HDs-MDSCs co-cultured with DB cells (n = 10) and SU-DHL-6 cells (n = 10)

Full size image

MDSCs in patients with DLBCL inhibit T cells proliferation and activation

Compared with the T cells co-cultured with HDs-MDSCs (3.39%), the proliferation ability of T cells co-cultured with DLBCL-MDSCs weakened significantly (2.60%; Fig. 3A). The CD69 (1.42% vs. 8.65%; Fig. 3B) and CD25 (8.42% vs. 1.50%; Fig. 3C) expression levels of T cells co-cultured with DLBCL-MDSCs were decreased. These findings indicate that DLBCL-MDSCs displayed an enhanced ability to inhibit T cells proliferation and activation.

Fig. 3
figure 3

MDSCs in patients with DLBCL patients inhibit T cells proliferation and activation. (A) Quantification of the Ki67 expression levels of T cells from HDs co-cultured with circulating DLBCL-MDSCs (n = 12) and HDs-MDSCs (n = 10). (B-C) The activation levels of T cells from HDs co-cultured with circulating DLBCL-MDSCs (n = 10) and HDs-MDSCs (n = 6)

Full size image

MDSCs in patients with DLBCL inhibit T cells function

The expression levels of cytokine secretion are critical biomarkers of T cells function [32, 33]. Granzyme B (10.98% vs. 15.03%; Fig. 4A), IFN-γ (0.36% vs. 0.85%; Fig. 4B), IL-17 (0.78% vs. 1.41%; Fig. 4C), and TNF-α (0.61% vs. 1.15%; Fig. 4D) expression levels were reduced in total T cells co-cultured with DLBCL-MDSCs compared to those co-cultured with HDs-MDSCs. These findings indicate that the ability to inhibit the T cells function of MDSCs in patients with DLBCL was enhanced.

Fig. 4
figure 4

MDSCs in patients with DLBCL inhibit T cells function. (A-D) Granzyme B, IFN-γ, IL-17, and TNF-α expression levels were reduced in total T cells co-cultured with DLBCL-MDSCs (n = 10) compared to those co-cultured with HDs-MDSCs (n = 6)

Full size image

Transcriptome analysis of MDSCs in patients with DLBCL

RNA transcriptome sequencing analysis was conducted on DLBCL-MDSCs and HDs-MDSCs to investigate the molecular mechanisms underlying the abnormalities of DLBCL-MDSCs. The hierarchical clustering analysis of differentially expressed genes (DEGs) revealed that DLBCL-MDSCs exhibited 976 upregulated and 3526 downregulated DEGs compared to HDs-MDSCs (fold change > 2, Fig. 5A, 5).

Fig. 5
figure 5

Transcriptome analysis of MDSCs in patients with DLBCL. (A) Volcano plot analysis showed differentially expressed genes (fold change > 2). (B) Heatmap of differentially expressed genes in RNA sequencing data from MDSCs of DLBCL patients and HDs. (C-D) GO and KEGG enrichment analyses showed significantly enrichment pathways of differentially expressed genes based on their functional categorization. (E) GSEA revealed 8 dysregulated pathways in MDSCs from DLBCL patients

Full size image

GO enrichment analysis demonstrated that the DEGs were notably enriched in immune regulation, T cells functions, cell processes, phosphorylation, and nitric oxide biosynthesis (Fig. 5C). KEGG enrichment analysis revealed that DEGs are linked to various immune-related signaling pathways, including antigen processing and presentation, TCR receptor signaling pathway, and IL-17 signaling pathway. Additionally, KEGG analysis identified associations with natural killer cell-mediated cytotoxicity, cell apoptosis, autophagy, and other cellular processes (Fig. 5D). GSEA enrichment analysis revealed that the glutathione metabolism, membrane potential stability, and oxidative phosphorylation pathways in DLBCL-MDSCs were upregulated. Simultaneously, the downregulated pathways were associated with apoptosis, autophagy regulation (Fig. 5E).

Association between MDSCs and clinical pathology in patients with DLBCL

The clinicopathological data of 65 newly diagnosed patients with DLBCL were analyzed (Table 1). And the median follow-up time in this study is 13 months. The percentages of MDSCs were higher in patients with stages III–IV (49.84%) compared with those at stages I–II and was positively correlated with the Ann Abor Stages (35.53%; Fig. 6A). Additionally, DLBCL-MDSCs correlate with the serum LDH levels positively and patients with abnormal LDH levels (58.43%) had a higher proportion of MDSCs than those with normal LDH levels (25.86%; Fig. 6B). Patients with high IPI scores (3 ≤ score ≤ 5) (58.87%) exhibited a significantly higher percentage of MDSCs than those with low IPI scores (0 ≤ score ≤ 2) (23.15%) and the two are positively correlated (Fig. 6C). However, no correlation was observed between the proportion of MDSCs and age, sex, cell of origin and B symptoms in patients with DLBCL. Then, we evaluated the circulating MDSCs of 11 out of the DLBCL patients who achieved complete response (CR) after chemotherapy. Notably, the percentages of MDSCs in these patients were significantly decreased (46.73% vs. 30.27%; Fig. 6D).

Table 1 Levels of MDSCs pathological indicators in newly diagnosed DLBCL patients
Full size table
Fig. 6
figure 6

Association between MDSCs and clinical pathology in patients with DLBCL. (A) The percentages of MDSCs in DLBCL patients with stages III–IV (n = 38) were higher than those at stages I–II (n = 27) and was positively correlated with the Ann Abor Stages. (B) DLBCL-MDSCs correlate with the serum LDH levels positively and patients with abnormal LDH levels (n = 36) had a higher proportion of MDSCs than those with normal LDH levels (n = 29). (C) High IPI score DLBCL patients (n = 40) had an increased frequency of MDSCs than those with low IPI score (n = 25) and the two are positively correlated. (D) The percentages of MDSCs in patients achieving CR were decreased compared to their initial diagnosis (n = 11)

Full size image

Discussion

This study identified the abnormal expansion of MDSCs in newly diagnosed patients with DLBCL. Subsequently, circulating DLBCL-MDSCs displayed elevated proliferation and decreased apoptosis levels compared to HDs. DLBCL-MDSCs exhibited an enhanced ability to inhibit T cells proliferation, activation and function. Transcriptome profiles suggested that DLBCL tumor cells stimulate MDSCs growth via activating specific signaling pathways. Furthermore, circulating DLBCL-MDSCs levels were associated with the Ann Arbor stage, serum LDH levels, and IPI scores. In the same patient with DLBCL who achieved CR after 6-course therapy, the level of MDSCs in peripheral blood is significantly decreased than at the time of initial diagnosis.

Whereas previous research has shown the increased expression of MDSCs in patients newly diagnosed with DLBCL [29], our study has added the detection of the proliferation and apoptosis levels of MDSCs in DLBCL. In additional, co-culturing data showed that the MDSCs proliferation level in the group co-cultured with DLBCL cell lines was increased, and the apoptosis level was decreased. Combined transcriptome sequencing data suggest that DLBCL tumor cells stimulate MDSCs growth by activating specific signaling pathways by secreting cyclooxygenase 2, prostaglandins, macrophage colony-stimulating factor, and vascular endothelial growth factor.

T cells can impede tumor growth through direct cytotoxicity towards tumor cells and modulate immune cell activity by secreting diverse immune regulatory molecules [30,31,32,33]. During inflammation, infection, and particularly in the presence of tumors, MDSCs migrate to injury sites and around tumor cells through the bloodstream, where they impede the normal functions of innate and adaptive immune cells [34,35,36]. Unlike the previous works [37, 38], our study not only fully explored the hyperfunction of immune suppression of DLBCL-MDSCs, but also explored possible molecular mechanisms at the transcriptional level through RNA sequencing, which needed comprehensively reported in the previous studies.

We further performed comparative analyses on transcriptomic profiles of circulating MDSCs between patients with DLBCL and HDs. The DEGs identified in this study were strongly associated with immune regulation, T cells function, oxidative phosphorylation, and nitric oxide biosynthesis. The differentially expressed pathways significantly enriched in DLBCL-MDSCs included apoptosis, antigen processing and presentation, TNF signaling pathway, TCR receptor signaling pathway, and IL-17 signaling pathway. Pathways associated with TCR, apoptosis, and autophagy regulation were downregulated in MDSCs from patients with DLBCL. The glutathione metabolism pathway was upregulated in DLBCL-MDSCs, which aroused our interest. Up-regulation of glutathione metabolism contributes to the maintenance of intracellular REDOX balance and is involved in the infiltration of immune cells and the regulation of immune responses [39, 40]. Subsequently, our research will employ methods such as gene knockout, transgenic animal models, and inhibitors or activators of glutathione synthesis to explore their effects on the metabolism and function of MDSCs.

Despite the meaningful findings of our study, it is essential to acknowledge several limitations that may influence the interpretation of our results. To ensure enhanced statistical power and generalizability of our findings, we will extend the follow-up period, collect sufficient relapsing cases, and include patients who do not respond to R-CHOP in the future. And it is necessary to comprehensively assess the relationship between MDSCs and the clinicopathological indicators (overall survival, laboratory, genetic, and imaging) of DLBCL and its prognosis. Moreover, our study focused only on total MDSCs analysis. Further studies are needed to explore the possible mechanisms for the differences in the functions of M-MDSCs and G-MDSCs, and whether the two subsets will interact and regulate each other. Additionally, this study has broadly explored the potential mechanisms and involved signaling pathways underlying the abnormal quantity and function of DLBCL-MDSCs at the transcriptional level. In the follow-up study, we will use gene editing technology, animal models and other methods to confirm these hypotheses.

Conclusion

The MDSCs derived from newly diagnosis DLBCL patients showed abnormal amplification and enhanced immunosuppressive function. And MDSCs were contributes to a compromised T cells immune response and involved in the progression of patients with DLBCL. This study offers valuable novel insights for developing immunotherapeutic strategies for DLBCL, specifically focusing on the potential benefits of targeting or modulating MDSCs function early in treatment.

Data availability

The RNA-seq data supporting the findings of this study have been deposited in the NCBI Sequence Read Archive (PRJNA1126079). The additional data used to arrive at conclusions can be obtained from the corresponding author on reasonable request.

Abbreviations

BM:

Bone marrow

DEGs:

Differentially expressed genes

DLBCL:

Diffuse large B-cell lymphoma

GCB:

Germinal center B-cell

GO:

Gene Ontology

GSEA:

Gene set enrichment analysis

HDs:

Healthy donors

IPI:

International prognostic index

IFN-γ:

Interferon-gamma

IL-17:

Interleukin-17

KEGG:

Kyoto Encyclopedia of genes and genomes

LDH:

Lactate dehydrogenase

MDSCs:

Myeloid-derived suppressor cells

PB:

Peripheral blood

TCR:

T cell receptor

TNF-α:

Tumor necrosis factor-alpha

References

  1. Lang R, Gill MJ. Diffuse large B-Cell lymphoma. N Engl J Med. 2021;384(23):2261–2.

    Article  PubMed  Google Scholar 

  2. Schwarzer A, Oliveira M, Kleppa MJ, Slattery SD, Anantha A, Cooper A, et al. Targeting aggressive B-cell lymphomas through Pharmacological activation of the mitochondrial protease OMA1. Mol Cancer Ther. 2023;22(11):1290–303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Ennishi D, Hsi ED, Steidl C, Scott DW. Toward a new molecular taxonomy of diffuse large B-cell lymphoma. Cancer Discov. 2020;10(9):1267–81.

    Article  CAS  PubMed  Google Scholar 

  4. Belada D, Kopeckova K, Bergua Burgues JM, Stevens D, André M, Persona EP, et al. Safety and efficacy of Tafasitamab with or without Lenalidomide added to first-line R-CHOP for DLBCL: the phase 1b First-MIND study. Blood. 2023;142(16):1348–58.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Stegemann M, Denker S, Schmitt CA. DLBCL 1L-What to expect beyond R-CHOP? Cancers (Basel). 2022;14(6).

  6. Autio M, Leivonen SK, Brück O, Karjalainen-Lindsberg ML, Pellinen T, Leppä S. Clinical impact of immune cells and their Spatial interactions in diffuse large B-Cell lymphoma microenvironment. Clin Cancer Res. 2022;28(4):781–92.

    Article  CAS  PubMed  Google Scholar 

  7. Lin AY, Gordon LI. Discovering the fibroblastic reticular cell in the immune tumor microenvironment in lymphoma. J Clin Invest. 2023;133(13).

  8. Susanibar-Adaniya S, Barta SK. 2021 Update on Diffuse large B cell lymphoma: A review of current data and potential applications on risk stratification and management. Am J Hematol. 2021;96(5):617– 29.

  9. Apodaca MC, Wright AE, Riggins AM, Harris WP, Yeung RS, Yu L, et al. Characterization of a whole blood assay for quantifying myeloid-derived suppressor cells. J Immunother Cancer. 2019;7(1):230.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Dong P, Chen L, Wu H, Huo J, Jiang Z, Shao Y, et al. Impaired immunosuppressive role of myeloid-derived suppressor cells in acquired aplastic anemia. Haematologica. 2022;107(12):2834–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Cassetta L, Bruderek K, Skrzeczynska-Moncznik J, Osiecka O, Hu X, Rundgren IM et al. Differential expansion of Circulating human MDSC subsets in patients with cancer, infection and inflammation. J Immunother Cancer. 2020;8(2).

  12. Li K, Shi H, Zhang B, Ou X, Ma Q, Chen Y, et al. Myeloid-derived suppressor cells as immunosuppressive regulators and therapeutic targets in cancer. Signal Transduct Target Ther. 2021;6(1):362.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Broughton TWK, ElTanbouly MA, Schaafsma E, Deng J, Sarde A, Croteau W, et al. Defining the signature of VISTA on myeloid cell chemokine responsiveness. Front Immunol. 2019;10:2641.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Ma T, Renz BW, Ilmer M, Koch D, Yang Y, Werner J et al. Myeloid-Derived suppressor cells in solid tumors. Cells. 2022;11(2).

  15. Ouzounova M, Lee E, Piranlioglu R, El Andaloussi A, Kolhe R, Demirci MF, et al. Monocytic and granulocytic myeloid derived suppressor cells differentially regulate Spatiotemporal tumour plasticity during metastatic cascade. Nat Commun. 2017;8:14979.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Zhang H, Maric I, DiPrima MJ, Khan J, Orentas RJ, Kaplan RN, et al. Fibrocytes represent a novel MDSC subset Circulating in patients with metastatic cancer. Blood. 2013;122(7):1105–13.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Jou E, Rodriguez-Rodriguez N, Ferreira AF, Jolin HE, Clark PA, Sawmynaden K, et al. An innate IL-25-ILC2-MDSC axis creates a cancer-permissive microenvironment for apc mutation-driven intestinal tumorigenesis. Sci Immunol. 2022;7(72):eabn0175.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Ni HH, Zhang L, Huang H, Dai SQ, Li J. Connecting METTL3 and intratumoural CD33(+) MDSCs in predicting clinical outcome in cervical cancer. J Transl Med. 2020;18(1):393.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Lai X, Liu XL, Pan H, Zhu MH, Long M, Yuan Y, et al. Light-Triggered efficient sequential drug delivery of biomimetic nanosystem for multimodal Chemo-, antiangiogenic, and Anti-MDSC therapy in melanoma. Adv Mater. 2022;34(10):e2106682.

    Article  PubMed  Google Scholar 

  20. Ozbay Kurt FG, Lasser S, Arkhypov I, Utikal J, Umansky V. Enhancing immunotherapy response in melanoma: myeloid-derived suppressor cells as a therapeutic target. J Clin Invest. 2023;133(13).

  21. Li YN, Wang ZW, Li F, Zhou LH, Jiang YS, Yu Y, et al. Inhibition of myeloid-derived suppressor cell arginase-1 production enhances T-cell-based immunotherapy against Cryptococcus neoformans infection. Nat Commun. 2022;13(1):4074.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Miret JJ, Kirschmeier P, Koyama S, Zhu M, Li YY, Naito Y, et al. Suppression of myeloid cell arginase activity leads to therapeutic response in a NSCLC mouse model by activating Anti-Tumor immunity. J Immunother Cancer. 2019;7(1):32.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Li S, Xu F, Ren X, Tan L, Fu C, Wu Q, et al. H(2)S-Reactivating antitumor immune response after microwave thermal therapy for Long-Term tumor suppression. ACS Nano. 2023;17(19):19242–53.

    Article  CAS  PubMed  Google Scholar 

  24. de Ruiz-Fernández B, Moreno H, Valencia K, Perurena N, Ruedas P, Walle T, et al. Tumor ENPP1 (CD203a)/Haptoglobin Axis exploits Myeloid-Derived suppressor cells to promote Post-Radiotherapy local recurrence in breast Cancer. Cancer Discov. 2022;12(5):1356–77.

    Article  Google Scholar 

  25. Bi Y, Li J, Yang Y, Wang Q, Wang Q, Zhang X, et al. Human liver stem cells attenuate Concanavalin A-induced acute liver injury by modulating myeloid-derived suppressor cells and CD4(+) T cells in mice. Stem Cell Res Ther. 2019;10(1):22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Long X, Wong CC, Tong L, Chu ESH, Ho Szeto C, Go MYY, et al. Peptostreptococcus anaerobius promotes colorectal carcinogenesis and modulates tumour immunity. Nat Microbiol. 2019;4(12):2319–30.

    Article  PubMed  Google Scholar 

  27. Weber R, Fleming V, Hu X, Nagibin V, Groth C, Altevogt P, et al. Myeloid-Derived suppressor cells hinder the Anti-Cancer activity of immune checkpoint inhibitors. Front Immunol. 2018;9:1310.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Romano A, Parrinello NL, Vetro C, Forte S, Chiarenza A, Figuera A, et al. Circulating myeloid-derived suppressor cells correlate with clinical outcome in hodgkin lymphoma patients treated up-front with a risk-adapted strategy. Br J Haematol. 2015;168(5):689–700.

    Article  CAS  PubMed  Google Scholar 

  29. Azzaoui I, Uhel F, Rossille D, Pangault C, Dulong J, Le Priol J, et al. T-cell defect in diffuse large B-cell lymphomas involves expansion of myeloid-derived suppressor cells. Blood. 2016;128(8):1081–92.

    Article  CAS  PubMed  Google Scholar 

  30. Wu L, Jin Y, Zhao X, Tang K, Zhao Y, Tong L, et al. Tumor aerobic Glycolysis confers immune evasion through modulating sensitivity to T cell-mediated bystander killing via TNF-α. Cell Metab. 2023;35(9):1580–e969.

    Article  CAS  PubMed  Google Scholar 

  31. Krug J, Rodrian G, Petter K, Yang H, Khoziainova S, Guo W, et al. N-glycosylation regulates intrinsic IFN-γ resistance in colorectal cancer: implications for immunotherapy. Gastroenterology. 2023;164(3):392–e4065.

    Article  CAS  PubMed  Google Scholar 

  32. Barrat FJ, Crow MK, Ivashkiv LB. Interferon target-gene expression and epigenomic signatures in health and disease. Nat Immunol. 2019;20(12):1574–83.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Wang S, Shi X, Li J, Huang Q, Ji Q, Yao Y, et al. A small molecule selected from a DNA-Encoded library of natural products that binds to TNF-α and attenuates inflammation in vivo. Adv Sci (Weinh). 2022;9(21):e2201258.

    Article  PubMed  Google Scholar 

  34. Cheng Y, Ma XL, Wei YQ, Wei XW. Potential roles and targeted therapy of the CXCLs/CXCR2 axis in cancer and inflammatory diseases. Biochim Biophys Acta Rev Cancer. 2019;1871(2):289–312.

    Article  CAS  PubMed  Google Scholar 

  35. Nam S, Lee A, Lim J, Lim JS. Analysis of the expression and regulation of PD-1 protein on the surface of Myeloid-Derived suppressor cells (MDSCs). Biomol Ther (Seoul). 2019;27(1):63–70.

    Article  CAS  PubMed  Google Scholar 

  36. Stevenson MM, Valanparambil RM, Tam M. Myeloid-Derived suppressor cells: the expanding world of helminth modulation of the immune system. Front Immunol. 2022;13:874308.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Wu C, Wu X, Zhang X, Chai Y, Guo Q, Li L, et al. Prognostic significance of peripheral monocytic myeloid-derived suppressor cells and monocytes in patients newly diagnosed with diffuse large b-cell lymphoma. Int J Clin Exp Med. 2015;8(9):15173–81.

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Wang Z, Jiang R, Li Q, Wang H, Tao Q, Zhai Z. Elevated M-MDSCs in circulation are indicative of poor prognosis in diffuse large B-Cell lymphoma patients. J Clin Med. 2021;10(8).

  39. Guo W, Li K, Sun B, Xu D, Tong L, Yin H, et al. Dysregulated glutamate transporter SLC1A1 propels cystine uptake via Xc(-) for glutathione synthesis in lung Cancer. Cancer Res. 2021;81(3):552–66.

    Article  CAS  PubMed  Google Scholar 

  40. Kurniawan H, Franchina DG, Guerra L, Bonetti L, Baguet LS, Grusdat M, et al. Glutathione restricts Serine metabolism to preserve regulatory T cell function. Cell Metab. 2020;31(5):920–e367.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank Central Laboratory, Fujian Medical University Union Hospital, for providing the experimental platform and Jing Wei from BD Biosciences for technical assistance. We would like to thank Editage (www.editage.com) for English language editing.

Funding

This research was sponsored by the Joint Funds for the innovation of science and Technology, Fujian province (2023Y9122), the government-funded project of the construction of high-level laboratory (Min201704), the Fujian Provincial Health Technology Project (2022GGA022), Joint Funds for the Innovation of Science and Technology, Fujian Province (2020Y9096), the Nature Science Funding of Fujian Province (2021J05049).

Author information

Author notes

  1. Jingru Liu and Shucheng Chen contributed equally to this work.

Authors and Affiliations

  1. Central Laboratory, Fujian Medical University Union Hospital, Fuzhou, Fujian, 350001, China

    Jingru Liu, Shucheng Chen, Yanrong Huang, Kaiming Xu, Maoqing Tan, Wei Dai, Xiaoting Wang, Diyu Hou & Huifang Huang

  2. Department of Clinical Laboratory, Fujian Medical University Union Hospital, Fuzhou, Fujian, 350001, China

    Jiadi Chen

  3. School of Medical Technology and Engineering, Fujian Medical University, Fuzhou, Fujian, 350122, China

    Shucheng Chen & Yanrong Huang

  4. Fujian Provincial Key Laboratory on Hematology, Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, Fujian, 350001, China

    Shuxia Zhang

Authors
  1. Jingru Liu
    View author publications

    Search author on:PubMed Google Scholar

  2. Shucheng Chen
    View author publications

    Search author on:PubMed Google Scholar

  3. Yanrong Huang
    View author publications

    Search author on:PubMed Google Scholar

  4. Kaiming Xu
    View author publications

    Search author on:PubMed Google Scholar

  5. Maoqing Tan
    View author publications

    Search author on:PubMed Google Scholar

  6. Wei Dai
    View author publications

    Search author on:PubMed Google Scholar

  7. Xiaoting Wang
    View author publications

    Search author on:PubMed Google Scholar

  8. Diyu Hou
    View author publications

    Search author on:PubMed Google Scholar

  9. Shuxia Zhang
    View author publications

    Search author on:PubMed Google Scholar

  10. Jiadi Chen
    View author publications

    Search author on:PubMed Google Scholar

  11. Huifang Huang
    View author publications

    Search author on:PubMed Google Scholar

Contributions

JL, JC and HH designed the research. JL, SC analyzed the data; JL, JC and HH wrote the manuscript. JL, SC, YH and KX performed the experiments. MT, WD, XW, DH and SZ participated in collecting data and helped to draft the manuscript. All authors reviewed and approved the manuscript.

Corresponding authors

Correspondence to Jiadi Chen or Huifang Huang.

Ethics declarations

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Review Committee of Fujian Medical University Union Hospital (2021WSJK018). And written informed consents were obtained from each patient.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, J., Chen, S., Huang, Y. et al. Abnormal proportions and functions of myeloid-derived suppressor cells in peripheral blood of patients with diffuse large B-cell lymphoma. BMC Cancer 25, 771 (2025). https://doi.org/10.1186/s12885-025-14142-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12885-025-14142-8

Keywords

BMC Cancer

ISSN: 1471-2407

Contact us