Intratumor Heterogeneity of MIF Expression Correlates With Extramedullary Involvement of Multiple Myeloma

Xu, Jianguo; Yu, Nanhui; Zhao, Pan; Wang, Fangfang; Huang, Jingcao; Cui, Yushan; Ding, Hong; Yang, Yiqin; Gao, Yuhan; Pan, Ling; Chang, Hong; Wu, Yuzhang; Xiang, Bing; Gong, Yuping; Xiao, Shuai; Hou, Li; Xie, Liping; Niu, Ting; Liu, Ting; Zhang, Li; Liu, Weiping; Zhang, Wenyan; Qu, Ying; Lin, Wei; Zhu, Yimin; Zhao, Sha; Zheng, Yuhuan

doi:10.3389/fonc.2021.694331

Cited by 4 publications

(3 citation statements)

References 49 publications

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“…MIF has been shown to directly promote disease progression in many malignancies, including MM. [ 42 43 44 ] MIF also reshaped the macrophage phenotype to an immunosuppressed status, which promotes disease progression in MM. [ 45 ] Templin et al [ 46 ] have noted that IL16 promotes the malignant phenotype of myeloma cells through different mechanisms.…”

Section: Discussionmentioning

confidence: 99%

Identification of potential immune-related mechanisms related to the development of multiple myeloma

Wang,

Zhang,

et al. 2024

Chinese Medical Journal

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Background: Although significant advances have been made in the treatment of multiple myeloma (MM), leading to unprecedented response and survival rates among patients, the majority eventually relapse, and a cure remains elusive. This situation is closely related to an incomplete understanding of the immune microenvironment, especially monocytes/macrophages in patients with treatment-naïve MM. The aim of this study was to provide insight into the immune microenvironment, especially monocytes/macrophages, in patients with treatment-naïve MM. Methods: This study used the single-cell RNA sequencing (scRNA-seq) data of both patients with MM and heathy donors to identify immune cells, including natural killer (NK) cells, T cells, dendritic cells (DCs), and monocytes/macrophages. Transcriptomic data and flow cytometry analysis of monocytes/macrophages were used to further examine the effect of monocytes/macrophages in treatment-naïve MM patients. Results: A significant difference was observed between the bone marrow (BM) immune cells of the healthy controls and treatment-naïve MM patients through scRNA-seq. It is noteworthy that, through an scRNA-seq data analysis, this study found that interferon (IFN)-induced NK/T cells, terminally differentiated effector memory (TEMRA) cells, T-helper cells characterized by expression of IFN-stimulated genes (ISG+Th cells), IFN-responding exhausted T cells, mannose receptor C-type 1 (MRC1)+ DCs, IFN-responding DCs, MHCII+ DCs, and immunosuppressive monocytes/macrophages are enriched in patients with treatment-naïve MM. Significantly, transcriptomic data of monocytes/macrophages demonstrated that “don’t eat me”-related genes and IFN-induced genes increase in treatment-naïve MM patients. Furthermore, scRNA-seq, transcriptomic data, and flow cytometry also showed an increased proportion of CD16+ monocytes/macrophages and expression level of CD16. Cell–cell communication analysis indicated that monocytes/macrophages, especially the migration inhibitory factor (MIF) and interleukin 16 (IL-16) signaling pathway, are key players in treatment-naïve MM patients. Conclusions: Our findings provide a comprehensive and in-depth molecular characterization of BM immune cell census in MM patients, especially for monocytes/macrophages. Targeting macrophages may be a novel treatment strategy for patients with MM.

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Section: Discussionmentioning

confidence: 99%

Identification of potential immune-related mechanisms related to the development of multiple myeloma

Wang,

Zhang,

et al. 2024

Chinese Medical Journal

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“…Previous studies indicated that APRIL expressed by monocytes/macrophages is a ligand of BCMA expressed by multiple myeloma cells, which can rescue interleukin 6 (IL-6)–dependent MM cell lines from apoptosis following IL-6 deprivation, stimulate MM cell growth via cyclin D-dependent G1/S cell cycle progression and induced immunosuppression in the bone marrow microenvironment [ 75 – 79 ]. Macrophage migration inhibitory factor (MIF) has been shown to promote disease progression directly in many malignancies, including multiple myeloma (MM) [ 80 – 82 ]. MIF also reshaped the macrophage phenotype to immunosuppressed status, which then promotes disease progression in MM [ 83 ].…”

Section: Discussionmentioning

confidence: 99%

Identification of potential resistance mechanisms and therapeutic targets for the relapse of BCMA CAR-T therapy in relapsed/refractory multiple myeloma through single-cell sequencing

Zhang

Cao

et al. 2023

Exp Hematol Oncol

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Background BCMA CAR-T is highly effective for relapsed/refractory multiple myeloma(R/R-MM) and significantly improves the survival of patients. However, the short remission time and high relapse rate of MM patients treated with BCMA CAR-T remain bottlenecks that limit long-term survival. The immune microenvironment of the bone marrow (BM) in R/R-MM may be responsible for this. The present study aims to present an in-depth analysis of resistant mechanisms and to explore potential novel therapeutic targets for relapse of BCMA CAR-T treatment via single-cell RNA sequencing (scRNA-seq) of BM plasma cells and immune cells. Methods This study used 10X Genomic scRNA-seq to identify cell populations in R/R-MM CD45+ BM cells before BCMA CAR-T treatment and relapse after BCMA CAR-T treatment. Cell Ranger pipeline and CellChat were used to perform detailed analysis. Results We compared the heterogeneity of CD45+ BM cells before BCMA CAR-T treatment and relapse after BCMA CAR-T treatment. We found that the proportion of monocytes/macrophages increased, while the percentage of T cells decreased at relapse after BCMA CAR-T treatment. We then reclustered and analyzed the alterations in plasma cells, T cells, NK cells, DCs, neutrophils, and monocytes/macrophages in the BM microenvironment before BCMA CAR-T treatment and relapse after BCMA CAR-T treatment. We show here that the percentage of BCMA positive plasma cells increased at relapse after BCMA CAR-T cell therapy. Other targets such as CD38, CD24, SLAMF7, CD138, and GPRC5D were also found to be expressed in plasma cells of the R/R-MM patient at relapse after BCMA CAR-T cell therapy. Furthermore, exhausted T cells, TIGIT+NK cells, interferon-responsive DCs, and interferon-responsive neutrophils, increased in the R/R-MM patient at relapse after BCMA CAR-T cell treatment. Significantly, the proportion of IL1βhi Mφ, S100A9hi Mφ, interferon-responsive Mφ, CD16hi Mφ, MARCO hi Mφ, and S100A11hi Mφ significantly increased in the R/R-MM patient at relapse after BCMA CAR-T cell therapy. Cell–cell communication analysis indicated that monocytes/macrophages, especially the MIF and APRIL signaling pathway are key players in R/R-MM patient at relapse after BCMA CAR-T cell therapy. Conclusion Taken together, our data extend the understanding of intrinsic and extrinsic relapse of BCMA CAR-T treatment in R/R-MM patient and the potential mechanisms involved in the alterations of antigens and the induced immunosuppressive microenvironment, which may provide a basis for the optimization of BCMA CAR-T strategies. Further studies should be performed to confirm these findings.

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“…MIF (Macrophage Migration Inhibitory Factor) has been shown to accelerates the development of the disease in multiple myeloma. MM patients with high MIF had a worse prognosis (Wang et al, 2020;Xu et al, 2021). A number of studies have shown that PLA2G4A (placental phospholipase A24A is involved in the biological procedure of stress response in various diseases (Brien et al, 2017;Zhang et al, 2018;Mishra et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of prognosis of cuproptosis-related oxidative stress genes in multiple myeloma

Yao

Yin

et al. 2023

Front. Genet.

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Introduction: Multiple myeloma (MM) is a highly heterogeneous hematologic malignancy. The patients’ survival outcomes vary widely. Establishing a more accurate prognostic model is necessary to improve prognostic precision and guide clinical therapy.Methods: We developed an eight-gene model to assess the prognostic outcome of MM patients. Univariate Cox analysis, Least absolute shrinkage and selection operator (LASSO) regression, and multivariate Cox regression analyses were used to identify the significant genes and construct the model. Other independent databases were used to validate the model.Results: The results showed that the overall survival of patients in the high-risk group was signifificantly shorter compared with that of those in the low-risk group. The eight-gene model demonstrated high accuracy and reliability in predicting the prognosis of MM patients.Discussion: Our study provides a novel prognostic model for MM patients based on cuproptosis and oxidative stress. The eight-gene model can provide valid predictions for prognosis and guide personalized clinical treatment. Further studies are needed to validate the clinical utility of the model and explore potential therapeutic targets.

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Intratumor Heterogeneity of MIF Expression Correlates With Extramedullary Involvement of Multiple Myeloma

Cited by 4 publications

References 49 publications

Identification of potential immune-related mechanisms related to the development of multiple myeloma

Identification of potential immune-related mechanisms related to the development of multiple myeloma

Identification of potential resistance mechanisms and therapeutic targets for the relapse of BCMA CAR-T therapy in relapsed/refractory multiple myeloma through single-cell sequencing

Comprehensive analysis of prognosis of cuproptosis-related oxidative stress genes in multiple myeloma

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