Gene expression signature predicting post-relapse survival of myeloma patients identified by co-culture of myeloma cells with osteoclasts and osteoblast progenitors
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA144803 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:To understand how interactions of myeloma cells with osteoclasts and mesenchymal stem cells in the bone marrow affect the clinical course of myeloma, we used microarrays to study changes in gene expression in freshly isolated myeloma plasma cells following co-cultures with osteoclasts (8 experiments) or with mesenchymal stem cells (13 experiments). Interaction with osteoclasts induced changes in the expression of 675 genes, and interaction with mesenchymal stem cells induced changes in the expression of 296 genes. Expression of only 58 genes commonly and similarly changed in both co-culture systems. Among these, we identified genes associated with overall, progression-free, and post-relapse survival, and developed survival prediction models. Gene expression data from 347 patients treated with total therapy 2 protocol, 433 with total therapy 3, and 98 patients who received various treatments (91 of them high-dose therapy with autologous stem cell support) were used for the analysis. Good predictive models were developed only for post-relapse survival, using genes involved in interaction with osteoclasts or with mesenchymal stem cells. The best predictive model used expression of first relapse of 33 probesets whose expression changed in myeloma cells following interaction with osteoclasts, with hazard ratios of 24, 20, and 12 for patients who relapsed following total therapy 2, total therapy 3 and the various other treatments, respectively. Among the probesets used for prediction, only 10, representing 8 genes, were commonly changed after both co-culture systems. These could present favorable target for therapy. Global gene expression profiling of osteoclasts (OCs) before and after co-culture with primary multiple myeloma plasma cells (MMPCs) was done using Affymetrix microarrays. Eight MMPC and OC co-culture experiments were performed using MMPC isolated from 8 patients and OC prepared from 8 different patients.
2015-08-13 | E-GEOD-31156 | biostudies-arrayexpress
Project description:The paper describes a model of multiple myeloma.
Created by COPASI 4.26 (Build 213)
This model is described in the article:
A mathematical model of cell equilibrium and joint cell formation in multiple myeloma
M.A. Koenders, R. Saso
Journal of Theoretical Biology 390 (2016) 73–79
Abstract:
In Multiple Myeloma Bone Disease healthy bone remodelling is affected by tumour cells by means of paracrine cytokinetic signalling in such a way that osteoclast formation is enhanced and the growth of osteoblast cells inhibited. The participating cytokines are described in the literature. Osteoclast-induced myeloma cell growth is also reported. Based on existing mathematical models for healthy bone remo- delling a three-way equilibrium model is presented for osteoclasts, osteoblasts and myeloma cell populations to describe the progress of the illness in a scenario in which there is a secular increase in the cytokinetic interactive effectiveness of paracrine processes. The equilibrium state for the system is obtained. The paracrine interactive effectiveness is explored by parameter variation and the stable region in the parameter space is identified. Then recently-discovered joint myeloma–osteoclast cells are added to the model to describe the populations inside lytic lesions. It transpires that their presence expands the available parameter space for stable equilibrium, thus permitting a detrimental, larger population of osteoclasts and myeloma cells. A possible relapse mechanism for the illness is explored by letting joint cells dissociate. The mathematics then permits the evaluation of the evolution of the cell populations as a function of time during relapse.
To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models .
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide.
Please refer to CC0 Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000804 | BioModels
Project description:To understand how interactions of myeloma cells with osteoclasts and mesenchymal stem cells in the bone marrow affect the clinical course of myeloma, we used microarrays to study changes in gene expression in freshly isolated myeloma plasma cells following co-cultures with osteoclasts (8 experiments) or with mesenchymal stem cells (13 experiments). Interaction with osteoclasts induced changes in the expression of 675 genes, and interaction with mesenchymal stem cells induced changes in the expression of 296 genes. Expression of only 58 genes commonly and similarly changed in both co-culture systems. Among these, we identified genes associated with overall, progression-free, and post-relapse survival, and developed survival prediction models. Gene expression data from 347 patients treated with total therapy 2 protocol, 433 with total therapy 3, and 98 patients who received various treatments (91 of them high-dose therapy with autologous stem cell support) were used for the analysis. Good predictive models were developed only for post-relapse survival, using genes involved in interaction with osteoclasts or with mesenchymal stem cells. The best predictive model used expression of first relapse of 33 probesets whose expression changed in myeloma cells following interaction with osteoclasts, with hazard ratios of 24, 20, and 12 for patients who relapsed following total therapy 2, total therapy 3 and the various other treatments, respectively. Among the probesets used for prediction, only 10, representing 8 genes, were commonly changed after both co-culture systems. These could present favorable target for therapy. Global gene expression profiling of primary multiple myeloma plasma cells (MMPCs) before and after interaction with osteoclasts (OCs) was done using Affymetrix microarrays.
2019-08-21 | GSE31154 | GEO
Project description:To understand how interactions of myeloma cells with osteoclasts and mesenchymal stem cells in the bone marrow affect the clinical course of myeloma, we used microarrays to study changes in gene expression in freshly isolated myeloma plasma cells following co-cultures with osteoclasts (8 experiments) or with mesenchymal stem cells (13 experiments). Interaction with osteoclasts induced changes in the expression of 675 genes, and interaction with mesenchymal stem cells induced changes in the expression of 296 genes. Expression of only 58 genes commonly and similarly changed in both co-culture systems. Among these, we identified genes associated with overall, progression-free, and post-relapse survival, and developed survival prediction models. Gene expression data from 347 patients treated with total therapy 2 protocol, 433 with total therapy 3, and 98 patients who received various treatments (91 of them high-dose therapy with autologous stem cell support) were used for the analysis. Good predictive models were developed only for post-relapse survival, using genes involved in interaction with osteoclasts or with mesenchymal stem cells. The best predictive model used expression of first relapse of 33 probesets whose expression changed in myeloma cells following interaction with osteoclasts, with hazard ratios of 24, 20, and 12 for patients who relapsed following total therapy 2, total therapy 3 and the various other treatments, respectively. Among the probesets used for prediction, only 10, representing 8 genes, were commonly changed after both co-culture systems. These could present favorable target for therapy. Global gene expression profiling of osteoclasts (OCs) before and after co-culture with primary multiple myeloma plasma cells (MMPCs) was done using Affymetrix microarrays.
2015-08-13 | GSE31156 | GEO
Project description:Multiple myeloma is largely incurable, despite development of therapies that target myeloma cell-intrinsic pathways. Disease relapse is thought to originate from dormant myeloma cells, localized in specialized niches, which resist therapy and re-populate the tumor. However, little is known about the niche, and how it exerts cell-extrinsic control over myeloma cell dormancy and re-activation. In this study we track individual myeloma cells by intravital imaging as they colonize the endosteal niche, enter a dormant state and subsequently become activated to form colonies. We demonstrate that dormancy is a reversible state which is switched ‘on’ by engagement with bone lining cells or osteoblasts, and switched ‘off’ by osteoclasts remodeling the endosteal niche. Dormant myeloma cells are resistant to chemotherapy targeting dividing cells. The demonstration that the endosteal niche is pivotal in controlling myeloma cell dormancy highlights the potential for targeting cell-extrinsic mechanisms to overcome cell-intrinsic drug resistance and prevent disease relapse.
2015-11-30 | GSE57695 | GEO
Project description:To understand how interactions of myeloma cells with osteoclasts and mesenchymal stem cells in the bone marrow affect the clinical course of myeloma, we used microarrays to study changes in gene expression in freshly isolated myeloma plasma cells following co-cultures with osteoclasts (8 experiments) or with mesenchymal stem cells (13 experiments). Interaction with osteoclasts induced changes in the expression of 675 genes, and interaction with mesenchymal stem cells induced changes in the expression of 296 genes. Expression of only 58 genes commonly and similarly changed in both co-culture systems. Among these, we identified genes associated with overall, progression-free, and post-relapse survival, and developed survival prediction models. Gene expression data from 347 patients treated with total therapy 2 protocol, 433 with total therapy 3, and 98 patients who received various treatments (91 of them high-dose therapy with autologous stem cell support) were used for the analysis. Good predictive models were developed only for post-relapse survival, using genes involved in interaction with osteoclasts or with mesenchymal stem cells. The best predictive model used expression of first relapse of 33 probesets whose expression changed in myeloma cells following interaction with osteoclasts, with hazard ratios of 24, 20, and 12 for patients who relapsed following total therapy 2, total therapy 3 and the various other treatments, respectively. Among the probesets used for prediction, only 10, representing 8 genes, were commonly changed after both co-culture systems. These could present favorable target for therapy. Global gene expression profiling of primary multiple myeloma plasma cells (MMPCs) and mesenchymal stem cells (MSCs) before and after co-culture was done using Affymetrix microarrays. Thirteen MMPC and MSC co-culture experiments using MMPCs from 8 patients and MSCs from 5 healthy donors were performed.
2015-08-13 | E-GEOD-31159 | biostudies-arrayexpress
Project description:To understand how interactions of myeloma cells with osteoclasts and mesenchymal stem cells in the bone marrow affect the clinical course of myeloma, we used microarrays to study changes in gene expression in freshly isolated myeloma plasma cells following co-cultures with osteoclasts (8 experiments) or with mesenchymal stem cells (13 experiments). Interaction with osteoclasts induced changes in the expression of 675 genes, and interaction with mesenchymal stem cells induced changes in the expression of 296 genes. Expression of only 58 genes commonly and similarly changed in both co-culture systems. Among these, we identified genes associated with overall, progression-free, and post-relapse survival, and developed survival prediction models. Gene expression data from 347 patients treated with total therapy 2 protocol, 433 with total therapy 3, and 98 patients who received various treatments (91 of them high-dose therapy with autologous stem cell support) were used for the analysis. Good predictive models were developed only for post-relapse survival, using genes involved in interaction with osteoclasts or with mesenchymal stem cells. The best predictive model used expression of first relapse of 33 probesets whose expression changed in myeloma cells following interaction with osteoclasts, with hazard ratios of 24, 20, and 12 for patients who relapsed following total therapy 2, total therapy 3 and the various other treatments, respectively. Among the probesets used for prediction, only 10, representing 8 genes, were commonly changed after both co-culture systems. These could present favorable target for therapy. Global gene expression profiling of primary multiple myeloma plasma cells (MMPCs) and mesenchymal stem cells (MSCs) before and after co-culture was done using Affymetrix microarrays.
2015-08-13 | GSE31159 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2015-08-13 | E-GEOD-31162 | biostudies-arrayexpress
Project description:This SuperSeries is composed of the SubSeries listed below.
2015-08-13 | GSE31162 | GEO
Project description:In this study we addressed subclonal evolutionary process after treatment and subsequent relapse in multiple myeloma (MM) in a cohort of 24 MM patients treated either with conventional chemotherapy or with the proteasome inhibitor, bortezomib. Because MM is a highly heterogeneous disease coupled with a large number of DNA copy number alterations (CNAs) and loss of heterozygosity (LOH), we focused our study on the secondary genetic events: 1q21 gain, NF-kB activating mutations, RB1 and TP53 deletions, that seem to reflect progression. By using genome-wide high resolution SNP arrays we identified subclones with nonlinear complex evolutionary histories in a third of patients with myeloma, the relapse clone apparently derived from a minor subclone at diagnosis. Such reordering of the spectrum of genetic lesions during therapy is likely to reflect selection of genetically distinct subclones not initially competitive against the dominant population that survived chemotherapy, thrived and acquired new anomalies. In addition we found that emergence of minor subclones at relapse was significantly associated with bortezomib treatment. Altogether, these data support the idea of new strategy of future clinical trials in MM that would combine targeted therapy and subpopulations control to eradicate all myeloma subclones in order to obtain long-term remission. This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2013-02-13 | E-GEOD-37469 | biostudies-arrayexpress