Bone Marrow Monocyte/Macrophage Derived Activin A Mediates the Osteoclastogenic Effects of IL-3 in Myeloma
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE41992 | GEO | 2014/11/01
SECONDARY ACCESSION(S): PRJNA178719
REPOSITORIES: GEO
Similar Datasets
Project description:Myeloma bone disease is characterized by tremendous bone destruction with suppressed bone formation. IL-3 is a multifunctional cytokine that increases myeloma cell growth and osteoclast proliferation while inhibiting osteoblast differentiation. While IL-3 appears to be an attractive therapeutic target for myeloma, attempts at targeting IL-3 have been unsuccessful due to IL-3M-bM-^@M-^Ys effects on normal hematopoiesis. Thus identification of IL-3M-bM-^@M-^Ys downstream effects in MMBD is important for effective targeting of this cytokine in MM. Here we demonstrated that treatment of myeloma patient CD14+ bone marrow monocyte / macrophages with IL-3 induces high levels of Activin A (ActA), a pluripotent TGF-M-NM-2 superfamily member that, like IL-3, modulates MMBD by enhancing osteoclastogenesis and inhibiting osteoblasts. We show that IL-3 induced osteoclastogenesis is mediated by ActA and is RANKL independent. Additionally, IL-3 induced ActA secretion is greatest early in osteoclastogenesis and ActA acts early in osteoclastogenesis. Therefore we suggest that therapies targeting ActA production should block IL-3M-bM-^@M-^Ys effects in myeloma bone disease. Investigate the mediators of IL-3M-bM-^@M-^Ys effects on bone remodeling in myeloma we performed gene expression profiling using Affymetrix GeneChip analysis of IL-3 treated CD14+ peripheral blood from healthy donor.
2014-11-01 | E-GEOD-41992 | biostudies-arrayexpress
Project description:The myeloma bone marrow microenvironment drives proliferation of malignant plasma cells and promotes resistance to therapy. Interleukin-6 (IL-6) and downstream JAK/STAT signaling are thought to be central components of these microenvironment-induced phenotypes. In a prior drug repurposing screen, we identified tofacitinib, a pan-JAK inhibitor FDA-approved for rheumatoid arthritis, as an agent that may reverse the tumor-stimulating effects of bone marrow mesenchymal stromal cells.Here, we validated both in vitro, in stromal-responsive human myeloma cell lines, and in vivo, in orthotopic disseminated murine xenograft models of myeloma, that tofacitinib showed both single-agent and combination therapeutic efficacy in myeloma models. Surprisingly, we found that ruxolitinib, an FDA-approved agent targeting JAK1 and JAK2, did not lead to the same anti-myeloma effects. Combination with a novel irreversible JAK3-selective inhibitor also did not rescue ruxolitinib effects. RNA-seq and unbiased phosphoproteomics revealed that marrow stromal cells drive a JAK/STAT-mediated proliferative program in myeloma plasma cells, and tofacitinib reversed the large majority of these pro-growth signals. Taken together, our results suggest that tofacitinib specifically reverses the growth-promoting effects of the tumor microenvironment through blocking an IL-6-mediated signaling axis. As tofacitinib is already FDA-approved, these results can be rapidly translated into potential clinical benefits for myeloma patients.
2018-10-24 | PXD006581 | Pride
Project description:Multiple myeloma is a plasma cell malignancy that is currently incurable with conventional therapies. Following the success of CD19-targeted chimeric antigen receptor (CAR) T-cells in leukemia and lymphoma, CAR T-cells targeting B-cell maturation antigen (BCMA) more recently demonstrated impressive activity in relapsed and refractory myeloma patients. However, BCMA-directed therapy can fail due to low expression of BCMA on myeloma cells, suggesting that novel approaches to better address antigen-low disease may improve patient outcomes. We hypothesized that engineered secretion of the pro-inflammatory cytokine interleukin-18 (IL-18) and multi-antigen targeting could improve CAR T-cell activity against BCMA-low myeloma. In a syngeneic murine model of myeloma, CAR T-cells targeting the myeloma-associated antigens BCMA and B-cell activating factor (BAFF-R) failed to eliminate myeloma when these antigens were weakly expressed. In contrast, IL-18-secreting CAR T-cells targeting these antigens promoted myeloma clearance. IL-18-secreting CAR T-cells developed an effector-like T-cell phenotype, promoted interferon-gamma production, reprogrammed the myeloma bone marrow microenvironment through type I and II interferon signaling, and utilized macrophages to mediate anti-myeloma activity. Simultaneous targeting of weakly expressed BCMA and BAFF-R with dual-CAR T-cells enhanced T-cell:target cell avidity, increased overall CAR signal strength, and stimulated anti-myeloma activity. Dual-antigen targeting augmented CAR T-cell secretion of engineered IL-18 and facilitated elimination of larger myeloma burdens in vivo. Our results demonstrate that combination of engineered IL-18 secretion and multi-antigen targeting can eliminate myeloma with weak antigen expression through distinct mechanisms.
2024-05-15 | GSE261852 | GEO
Project description:Multiple myeloma is a plasma cell malignancy that is currently incurable with conventional therapies. Following the success of CD19-targeted chimeric antigen receptor (CAR) T-cells in leukemia and lymphoma, CAR T-cells targeting B-cell maturation antigen (BCMA) more recently demonstrated impressive activity in relapsed and refractory myeloma patients. However, BCMA-directed therapy can fail due to low expression of BCMA on myeloma cells, suggesting that novel approaches to better address antigen-low disease may improve patient outcomes. We hypothesized that engineered secretion of the pro-inflammatory cytokine interleukin-18 (IL-18) and multi-antigen targeting could improve CAR T-cell activity against BCMA-low myeloma. In a syngeneic murine model of myeloma, CAR T-cells targeting the myeloma-associated antigens BCMA and B-cell activating factor (BAFF-R) failed to eliminate myeloma when these antigens were weakly expressed. In contrast, IL-18-secreting CAR T-cells targeting these antigens promoted myeloma clearance. IL-18-secreting CAR T-cells developed an effector-like T-cell phenotype, promoted interferon-gamma production, reprogrammed the myeloma bone marrow microenvironment through type I and II interferon signaling, and utilized macrophages to mediate anti-myeloma activity. Simultaneous targeting of weakly expressed BCMA and BAFF-R with dual-CAR T-cells enhanced T-cell:target cell avidity, increased overall CAR signal strength, and stimulated anti-myeloma activity. Dual-antigen targeting augmented CAR T-cell secretion of engineered IL-18 and facilitated elimination of larger myeloma burdens in vivo. Our results demonstrate that combination of engineered IL-18 secretion and multi-antigen targeting can eliminate myeloma with weak antigen expression through distinct mechanisms.
2024-05-15 | GSE246682 | GEO
Project description:This a model from the article:
A mathematical model of bone remodeling dynamics for normal bone cell populations and myeloma bone disease
Bruce P Ayati, Claire M Edwards, Glenn F Webb and John P Wikswo.
Biology Direct2010 Apr 20;5(28).
20406449,
Abstract:
BACKGROUND:
Multiple myeloma is a hematologic malignancy associated with the development of a destructive osteolytic bone disease.
RESULTS:
Mathematical models are developed for normal bone remodeling and for the dysregulated bone remodeling that occurs in myeloma bone disease. The models examine the critical signaling between osteoclasts (bone resorption) and osteoblasts (bone formation). The interactions of osteoclasts and osteoblasts are modeled as a system of differential equations for these cell populations, which exhibit stable oscillations in the normal case and unstable oscillations in the myeloma case. In the case of untreated myeloma, osteoclasts increase and osteoblasts decrease, with net bone loss as the tumor grows. The therapeutic effects of targeting both myeloma cells and cells of the bone marrow microenvironment on these dynamics are examined.
CONCLUSIONS:
The current model accurately reflects myeloma bone disease and illustrates how treatment approaches may be investigated using such computational approaches.
Note:
The paper describes three models 1) Zero-dimensional Bone Model without Tumour, 2) Zero-dimensional Bone Model with Tumour and 3) Zero-dimensional Bone Model with Tumour and Drug Treatment. This model corresponds to the Zero-dimensional Bone Model without Tumour.
Typos in the publication:
Equation (4): The first term should be (β1/α1)^(g12/Γ) and not (β2/α2)^(g12/Γ)
Equation (14): The first term should be (β1/α1)^(((g12/(1+r12))/Γ) and not (β2/α2)^(((g12/(1+r12))/Γ)
Equation (13): The first term should be (β1/α1)^((1-g22+r22)/Γ) and not (β1/α1)^((1-g22-r22)/Γ)
All these corrections has been implemented in the model, with the authors agreement.
Beyond these, there are several mismatches between the equation numbers that are mentioned in for each equation and the reference that has been made to these equations in the figure legend.
2024-09-02 | BIOMD0000000401 | BioModels
Project description:This a model from the article:
A mathematical model of bone remodeling dynamics for normal bone cell populations and myeloma bone disease
Bruce P Ayati, Claire M Edwards, Glenn F Webb and John P Wikswo.
Biology Direct2010 Apr 20;5(28).
20406449,
Abstract:
BACKGROUND:
Multiple myeloma is a hematologic malignancy associated with the development of a destructive osteolytic bone disease.
RESULTS:
Mathematical models are developed for normal bone remodeling and for the dysregulated bone remodeling that occurs in myeloma bone disease. The models examine the critical signaling between osteoclasts (bone resorption) and osteoblasts (bone formation). The interactions of osteoclasts and osteoblasts are modeled as a system of differential equations for these cell populations, which exhibit stable oscillations in the normal case and unstable oscillations in the myeloma case. In the case of untreated myeloma, osteoclasts increase and osteoblasts decrease, with net bone loss as the tumor grows. The therapeutic effects of targeting both myeloma cells and cells of the bone marrow microenvironment on these dynamics are examined.
CONCLUSIONS:
The current model accurately reflects myeloma bone disease and illustrates how treatment approaches may be investigated using such computational approaches.
Note:
The paper describes three models 1) Zero-dimensional Bone Model without Tumour, 2) Zero-dimensional Bone Model with Tumour and 3) Zero-dimensional Bone Model with Tumour and Drug Treatment. This model corresponds to the Zero-dimensional Bone Model with Tumour.
Typos in the publication:
Equation (4): The first term should be (β1/α1)^(g12/Γ) and not (β2/α2)^(g12/Γ)
Equation (14): The first term should be (β1/α1)^(((g12/(1+r12))/Γ) and not (β2/α2)^(((g12/(1+r12))/Γ)
Equation (13): The first term should be (β1/α1)^((1-g22+r22)/Γ) and not (β1/α1)^((1-g22-r22)/Γ)
All these corrections has been implemented in the model, with the authors agreement.
Beyond these, there are several mismatches between the equation numbers that are mentioned in for each equation and the reference that has been made to these equations in the figure legend.
2024-09-02 | BIOMD0000000402 | BioModels
Project description:This a model from the article:
A mathematical model of bone remodeling dynamics for normal bone cell populations and myeloma bone disease
Bruce P Ayati, Claire M Edwards, Glenn F Webb and John P Wikswo.
Biology Direct2010 Apr 20;5(28).
20406449,
Abstract:
BACKGROUND:
Multiple myeloma is a hematologic malignancy associated with the development of a destructive osteolytic bone disease.
RESULTS:
Mathematical models are developed for normal bone remodeling and for the dysregulated bone remodeling that occurs in myeloma bone disease. The models examine the critical signaling between osteoclasts (bone resorption) and osteoblasts (bone formation). The interactions of osteoclasts and osteoblasts are modeled as a system of differential equations for these cell populations, which exhibit stable oscillations in the normal case and unstable oscillations in the myeloma case. In the case of untreated myeloma, osteoclasts increase and osteoblasts decrease, with net bone loss as the tumor grows. The therapeutic effects of targeting both myeloma cells and cells of the bone marrow microenvironment on these dynamics are examined.
CONCLUSIONS:
The current model accurately reflects myeloma bone disease and illustrates how treatment approaches may be investigated using such computational approaches.
Note:
The paper describes three models 1) Zero-dimensional Bone Model without Tumou
r, 2) Zero-dimensional Bone Model with Tumour and 3) Zero-dimensional Bone Model with Tumour and Drug Treatment. This model corresponds to the Zero-dimensional Bo
ne Model with Tumour and Drug Treatment.
Typos in the publication:
Equation (4): The first term should be (β1/α1)^(g12/Γ) and not (β2/α2)^(g12/Γ)
Equation (14): The first term should be (β1/α1)^(((g12/(1+r12))/Γ) and not (β2/α2)^(((g12/(1+r12))/Γ)
Equation (13): The first term should be (β1/α1)^((1-g22+r22)/Γ) and not (β1/α1)^((1-g22-r22)/Γ)
All these corrections has been implemented in the model, with the authors agreement.
Beyond these, there are several mismatches between the equation numbers that are mentioned in for each equation and the reference that has been made to these equations in the figure legend.
2024-09-02 | BIOMD0000000403 | BioModels
Project description:Purpose: Among the diverse cytokines involved in osteoclast differentiation, IL-3 has been shown to inhibit RANKL-induced osteoclastogenesis. However, the mechanism underlying IL-3-mediated inhibition of osteoclast differentiation is not fully understood. In the present study, we demonstrate that IL-3 activation of STAT5 inhibits RANKL-induced osteoclastogenesis through the induction of Id genes. Methods: To investigate the effect of STAT5 on osteoclast differentiation and IL-3-mediated inhibition of osteoclast differentiation, bone marrow derived macrophages isolated from STAT5 wild-type (Stat5fl/fl) or STAT5 cKO (STAT5;MX1-Cre) were differentiated to osteoclast in the presence of M-CSF and RANKL with or without IL-3; and bone marrow derived macrophges from STAT5 wild-type and STAT5 cKO were overexpressed with PMX-FIG (control) or STAT5A1*6 (constitutively active form of STAT5A) and differentiated to osteoclast. To analyze bone phenotype, femurs and tibiae of 16 week-old STAT5 wild-type and STAT5 cKO were subjected to micro CT analysis and histomorphometry, respectively. Results: Overexpression of STAT5 inhibited RANKL-induced osteoclastogenesis. However, RANKL did not regulate either expression or activation of STAT5 during osteoclast differentiation. STAT5 deficiency prevented IL-3-mediated inhibition of osteoclastogenesis, suggesting that STAT5 plays an important role in IL-3-mediated inhibition of osteoclast differentiation. In addition, IL-3-induced STAT5 activation upregulated expression of the Id1 and Id2 genes, which are negative regulators of osteoclastogenesis. Overexpression of ID1 or ID2 in STAT5-deficient cells reversed osteoclast development recovered from IL-3-mediated inhibition. Moreover, micro-computed tomography and histomorphometric analysis revealed that STAT5 conditional knockout mice showed reduced bone mass, with an increased number of osteoclasts. Furthermore, IL-3 inhibited RANKL-induced osteoclast differentiation less effectively in STAT5 conditional knockout mice than in wild-type mice in a RANKL injection model. Conclusion: Taken together, our results suggest that STAT5 is a key transcription factor for IL-3-mediated inhibition of RANKL-induced osteoclastogenesis through Id gene expression. Examination of 4 different combination of osteoclast differentiation condition of bone marrow derived macrophages.
2016-08-03 | E-GEOD-76988 | biostudies-arrayexpress
Project description:An aged immune system undergoes substantial changes where myelopoiesis dominates within the bone marrow. Monocytic-MDSCs (M-MDSCs) have been found to play an important role in osteoclastogenesis and bone resorption. In this study, we sought to provide a more comprehensive understanding of the osteoclastogenic potential of bone marrow M-MDSCs during normal aging through transcriptomic and metabolic changes. Using young mature and aged mice, detailed immunophenotypic analyses of myeloid cells revealed that the M-MDSCs were not increased in bone marrow, however M-MDSCS were significantly expanded in peripheral tissues. Although aged mice exhibited a similar number of M-MDSCs in bone marrow, these M-MDSCs had significantly higher osteoclastogenic potential and greater bone resorption capacity. Intriguingly, osteoclast progenitors from aged bone marrow M-MDSCs exhibited greater mitochondrial respiration rate and glucose metabolism. Further, transcriptomic analyses revealed the upregulation of mitochondrial oxidative phosphorylation and glucose metabolism genes. Interestingly, there was a 3-fold increase in Cd38 mRNA gene expression, consistent with the Mouse Aging Cell Atlas transcriptomic database. CD38 regulates NAD+ availability, and 78c, a small molecule inhibitor of CD38, reduced the mitochondrial oxygen consumption rate and glucose metabolism and inhibited the osteoclastogenic potential of aged mice bone marrow-derived M-MDSCs. These results indicate that the age-related increase in Cd38 expression in M-MDSCs bias the transcriptome of M-MDSCs towards osteoclastogenesis. This enhanced understanding of the mechanistic underpinnings of M-MDSCs and their osteoclastogenesis during aging could lead to new therapeutic approaches for age-related bone loss and promote healthy aging.
2024-09-16 | GSE252129 | GEO
Project description:The myeloma bone marrow microenvironment promotes proliferation of malignant plasma cells and resistance to therapy. Interleukin-6 (IL-6) and downstream JAK/STAT signaling are thought to be central components of these microenvironment-induced phenotypes. In a prior drug repurposing screen, we identified tofacitinib, a pan-JAK inhibitor FDA-approved for rheumatoid arthritis, as an agent that may reverse the tumor-stimulating effects of bone marrow mesenchymal stromal cells. Here, we validated both in vitro, in stromal-responsive human myeloma cell lines, and in vivo, in orthotopic disseminated murine xenograft models of myeloma, that tofacitinib showed both single-agent and combination therapeutic efficacy in myeloma models. Surprisingly, we found that ruxolitinib, an FDA-approved agent targeting JAK1 and JAK2, did not lead to the same anti-myeloma effects. Combination with a novel irreversible JAK3-selective inhibitor also did not enhance ruxolitinib effects. RNA-seq and unbiased phosphoproteomics revealed that marrow stromal cells stimulate a JAK/STAT-mediated proliferative program in myeloma plasma cells, and tofacitinib reversed the large majority of these pro-growth signals. Taken together, our results suggest that tofacitinib specifically reverses the growth-promoting effects of the tumor microenvironment through blocking an IL-6-mediated signaling axis. As tofacitinib is already FDA-approved, these results can be rapidly translated into potential clinical benefits for myeloma patients.
2017-05-26 | GSE99293 | GEO