Reprogrammed marrow adipocytes: an unexpected role in the genesis of myeloma-induced bone disease (ChIP-Seq)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE113642 | GEO | 2018/04/26
REPOSITORIES: GEO
Similar Datasets
Project description:Multiple myeloma is characterized by osteolytic lesions caused by osteoclast-mediated bone resorption and reduced bone formation. A unique feature of myeloma is a failure of bone healing following successful treatment. Identification of increased adipocyte numbers in marrow of successfully treated patients led us to demonstrate that normal marrow adipocytes, when co-cultured with myeloma cells, are reprogrammed and produce adipokines that activate osteoclastogenesis and suppress osteoblastogenesis. These adipocytes have reduced expression of peroxisome proliferator-activated receptor γ (PPARγ) mediated by recruitment of polycomb-repressive complex 2 (PRC2) via specificity protein 1, which modifies PPARγ promoter methylation at trimethyl lysine-27 histone H3. We confirmed the importance of PPARγ methylation by demonstrating that adipocyte-specific knockout of EZH2, a member of the PRC2, prevents adipocyte reprogramming and reverses bone changes in vivo. These results define a heretofore unrecognized role for adipocytes in genesis of myeloma-associated bone disease and that reversal of adipocyte reprogramming has therapeutic implications.
2018-04-18 | GSE113295 | GEO
Project description:Bone marrow -adipocytes (BMAs) have recently been implicated in accelerating bone metastatic cancers such as AML and breast cancer. Importantly, bone marrow adipose tissue (BMAT) expands with aging and obesity- two key risk factors in multiple myeloma (MM) disease prevalence- suggesting that BMAs influence and are influenced by myeloma cells in the marrow. Here we examined how myeloma cells affect adipocytes and provide evidence that MM cells alter adipocyte gene expression and cytokine secretion profiles, creating a “MM-associated” adipocyte (MM-adipocyte) phenotype. Our findings indicate that: (1) Multiple myeloma cells decrease BM adiposity in vitro, in myeloma animal models, and in clinical samples, (2) myeloma induces widespread gene expression and phenotypic changes in adipocytes in vitro, most notable, the induction of a senescent-like phenotype in BMAs, (3) MM-adipocytes affect myeloma cell cycle, drug sensitivity, and aggressiveness, illuminating a new driver of MM cell evolution in a drug resistant clone. We demonstrate that myeloma cells exposed to MM-adipocytes are rescued from dexamethasone-induced cell cycle arrest and have increased expression of FKBP5, a potential drug resistance gene. Our findings in patients confirm that BMAs are dynamic during myeloma disease progression (decrease during MM initiation, recover during disease remission) and that the interactions between BMAs and MM cells have previously unappreciated implications in the understanding and treatment of myeloma.
2021-03-10 | GSE140374 | GEO
Project description:The unique properties of the bone marrow allow for migration and proliferation of multipl myeloma (MM) cells, while also providing the perfect environment for development of quiescent, drug-resistant MM cell clones. Bone marrow adipocytes (BMAds), which have recently been identified as important contributors to systemic adipokine levels, bone strength, hematopoiesis, and progression of metastatic and primary bone marrow cancers, such as MM. Recent studies in myeloma suggest that BMAds can be reprogrammed by tumor cells to contribute to myeloma-induced bone disease, and reciprocally, BMAds support MM cells in vitro. Importantly, most data investigating BMAds have been generated using adipocytes derived by differentiating bone marrow-derived mesenchymal stromal cells (MSCs) into adipocytes in vitro using adipogenic media, due to the extreme technical challenges associated with isolating and culturing primary adipocytes. However, if studies could be performed with primary adipocytes, they likely will recapitulate in vivo biology better than MSC-derived adipocyte, as the differentiation process is artificial and differs from in vivo differentiation, and progenitor cell(s) of the primary BMAd may not be the same as the MSCs precursors used for adipogenic differentiation in vitro. Therefore, we developed and refined three methods for culturing primary BMAds (pBMAds): 2D coverslips, 2D transwells, and 3D silk scaffolds, all of which can be cultured alone or with MM cells to investigate bidirectional tumor-host signaling. To develop an in vitro model with a tissue-like structure to mimic the bone marrow microenvironment, we developed the first 3D, tissue engineered model utilizing pBMAds derived from human bone marrow. We found that pBMAds, which are extremely fragile, can be isolated and stably cultured in 2D for 10 days and in 3D for short term (~2 weeks) or long term (1 month) in vitro. To investigate the relationship between pBMAds and myeloma, MM cells can be added to investigate physical relationships through confocal imaging and soluble signaling molecules via mass spectrometry. In sum, we developed three in vitro cell culture systems to study primary bone marrow adipocytes and myeloma cells, which could be adapted to investigate many diseases and biological processes involving the bone marrow, including other bone-homing tumor types.
2023-01-04 | PXD032753 | Pride
Project description:We have identified a population of adipocytes in fat tissue that arise from bone marrow-derived progenitor cells. We used microarrays to compare the global gene expression patterns of the bone marrow progenitor-derived adipocytes as well as conventional white and brown adipocytes to evaluate the relationship between these adipocyte subpopulations. Gonadal fat tissue (for white adipocytes) and intrascapular fat tissue (for brown adipocytes) was digested with collagenase and adipocytes were recovered by centrifugation/flotation. Bone marrow derived adipocytes were isolated from the adipocyte fraction of gonadal fat tissue from mice receiving bone marrow tranplants from donors expressing either green fluorescent protein (GFP) or beta-galactosidase (LacZ) by flow cytometry.
2010-01-08 | E-GEOD-19757 | biostudies-arrayexpress
Project description:The nuclear receptor PPAR gamma is required for adipocyte differentiation, but its role in mature adipocytes is less clear. Here we report that knockdown of PPAR gamma expression in 3T3-L1 adipocytes returned the expression of most adipocyte genes towards preadipocyte levels. Consistently, down regulated but not up regulated genes showed strong enrichment of PPAR gamma binding. Surprisingly, not all adipocyte genes were reversed and the adipocyte morphology was maintained for an extended period after PPAR gamma depletion. To explain this, we focused on transcriptional regulators whose adipogenic regulation was not reversed upon PPAR gamma depletion. We identified GATA2, a transcription factor whose down-regulation early in adipogenesis is required for preadipocyte differentiation, remaining low after PPAR gamma knockdown. Forced expression of GATA2 in mature adipocytes complemented PPAR gamma depletion and impaired adipocyte functionality with a more preadipocyte- like gene expression profile. Ectopic expression of GATA2 in adipose tissue in vivo had similar effect on adipogenic gene expression. These results suggest that PPAR gamma-independent down regulation of GATA2 prevents reversion of mature adipocytes after PPAR gamma depletion. Experiment Overall Design: This dataset consists of three sample groups: preadipocytes, control siRNA treated adipocytes, and PPAR gamma siRNA treated adipocytes. Each sample group consists of three replicates samples. Each sample was hybridized to a separate array for a total of nine arrays. Experiment Overall Design: Technical replicates: Pread 1, Pread 2, Pread 3 Experiment Overall Design: Technical replicates: Cont siRNA 1, Cont siRNA 2, Cont siRNA 3 Experiment Overall Design: Technical replicates: PPAR gamma siRNA 1, PPAR gamma siRNA 2, PPAR gamma siRNA 3
2009-01-29 | E-GEOD-14004 | biostudies-arrayexpress
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 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 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:The nuclear receptor PPAR gamma is required for adipocyte differentiation, but its role in mature adipocytes is less clear. Here we report that knockdown of PPAR gamma expression in 3T3-L1 adipocytes returned the expression of most adipocyte genes towards preadipocyte levels. Consistently, down regulated but not up regulated genes showed strong enrichment of PPAR gamma binding. Surprisingly, not all adipocyte genes were reversed and the adipocyte morphology was maintained for an extended period after PPAR gamma depletion. To explain this, we focused on transcriptional regulators whose adipogenic regulation was not reversed upon PPAR gamma depletion. We identified GATA2, a transcription factor whose down-regulation early in adipogenesis is required for preadipocyte differentiation, remaining low after PPAR gamma knockdown. Forced expression of GATA2 in mature adipocytes complemented PPAR gamma depletion and impaired adipocyte functionality with a more preadipocyte- like gene expression profile. Ectopic expression of GATA2 in adipose tissue in vivo had similar effect on adipogenic gene expression. These results suggest that PPAR gamma-independent down regulation of GATA2 prevents reversion of mature adipocytes after PPAR gamma depletion. Keywords: cell type comparison, Gata2, PPAR gamma, adipocyte, preadipocytes, differentiation
2009-01-14 | GSE14004 | GEO
Project description:We have identified a population of adipocytes in fat tissue that arise from bone marrow-derived progenitor cells. We used microarrays to compare the global gene expression patterns of the bone marrow progenitor-derived adipocytes as well as conventional white and brown adipocytes to evaluate the relationship between these adipocyte subpopulations.
2010-01-08 | GSE19757 | GEO