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Dynamic imbalance between cancer cell subpopulations induced by Transforming Growth Factor Beta (TGF-β) is associated with a DNA methylome switch [expression array]

ABSTRACT: Dynamic imbalance between cancer cell subpopulations induced by Transforming Growth Factor Beta (TGF-β) is associated with a DNA methylome switch [expression array]

PROVIDER: PRJNA525351 | ENA |

REPOSITORIES: ENA

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Dynamic imbalance between cancer cell subpopulations induced by Transforming Growth Factor Beta (TGF-β) is associated with a DNA methylome switch [methylation]

Project description:Distinct subpopulations of neoplastic cells within tumors, including hepatocellular carcinoma (HCC), display pronounced ability to initiate new tumors and induce metastasis. Recent evidence suggests that signals from transforming growth factor beta (TGF-β) may increase the survival of these so called tumor initiating cells leading to poor HCC prognosis. However, how TGF-β establishes and modifies the key features of these cell subpopulations is not fully understood. In the present report we describe the differential DNA methylome of CD133-negative and CD133-expressing liver cancer cells. Next, we show that TGF-β is able to increase the proportion of CD133+ cells in liver cancer cell lines in a way that is stable and persistent across cell division. This process is associated with stable genome-wide changes in DNA methylation that persist through cell division. Differential methylation in response to TGF-β is under-represented at promoter CpG islands and enriched at gene bodies, including a locus in the body of the de novo DNA methyl-transferase DNMT3B gene. Moreover, phenotypic changes induced by TGF-β, including the induction of CD133, are impaired by siRNA silencing of de novo DNA methyl-transferases. Our study reveals a self-perpetuating crosstalk between TGF-β signaling and the DNA methylation machinery, which can be relevant in the establishment of cellular phenotypes. This is the first indication of the ability of TGF-β to induce genome-wide changes in DNA methylation, resulting in a stable change in the proportion of liver cancer cell subpopulations.

2019-03-05 | GSE127828 | GEO

Dynamic imbalance between cancer cell subpopulations induced by Transforming Growth Factor Beta (TGF-β) is associated with a DNA methylome switch [expression array]

2019-03-05 | GSE127763 | GEO

Dynamic imbalance between cancer cell subpopulations induced by Transforming Growth Factor Beta (TGF-β) is associated with a DNA methylome switch

Project description:Dynamic imbalance between cancer cell subpopulations induced by Transforming Growth Factor Beta (TGF-β) is associated with a DNA methylome switch

| PRJNA525597 | ENA

Dynamic imbalance between cancer cell subpopulations induced by Transforming Growth Factor Beta (TGF-β) is associated with a DNA methylome switch [methylation]

Project description:Dynamic imbalance between cancer cell subpopulations induced by Transforming Growth Factor Beta (TGF-β) is associated with a DNA methylome switch [methylation]

| PRJNA525600 | ENA

Spleen vs TGF-beta (transforming growth factor-beta) Treated B cell

Project description:total RNA from mouse (male c57BL/6) spleen labeled with Cy3 vs total RNA from mouse (male c57BL/6) B cells treated with TGF-beta (transforming growth factor-beta) labeled with Cy5- time course with repeats Keywords: ordered

2003-04-14 | GSE400 | GEO

Dynamic imbalance between cancer cell subpopulations induced by transforming growth factor beta (TGF-?) is associated with a DNA methylome switch.

Project description:Distinct subpopulations of neoplastic cells within tumors, including hepatocellular carcinoma (HCC), display pronounced ability to initiate new tumors and induce metastasis. Recent evidence suggests that signals from transforming growth factor beta (TGF-?) may increase the survival of these so called tumor initiating cells leading to poor HCC prognosis. However, how TGF-? establishes and modifies the key features of these cell subpopulations is not fully understood.In the present report we describe the differential DNA methylome of CD133-negative and CD133-expressing liver cancer cells. Next, we show that TGF-? is able to increase the proportion of CD133+ cells in liver cancer cell lines in a way that is stable and persistent across cell division. This process is associated with stable genome-wide changes in DNA methylation that persist through cell division. Differential methylation in response to TGF-? is under-represented at promoter CpG islands and enriched at gene bodies, including a locus in the body of the de novo DNA methyl-transferase DNMT3B gene. Moreover, phenotypic changes induced by TGF-?, including the induction of CD133, are impaired by siRNA silencing of de novo DNA methyl-transferases.Our study reveals a self-perpetuating crosstalk between TGF-? signaling and the DNA methylation machinery, which can be relevant in the establishment of cellular phenotypes. This is the first indication of the ability of TGF-? to induce genome-wide changes in DNA methylation, resulting in a stable change in the proportion of liver cancer cell subpopulations.

| S-EPMC4070873 | biostudies-other

Dynamic imbalance between cancer cell subpopulations induced by Transforming Growth Factor Beta (TGF-β) is associated with a DNA methylome switch

Project description:This SuperSeries is composed of the SubSeries listed below.

2019-03-05 | GSE127829 | GEO

Expression data from A549 cells after treatment with flagellin and transforming growth factor beta 1

Project description:We have examined the changes in gene expression aftert reatment of A549 cells, a cultured alveolar epithelial cells, with flagellin and transforming growth factor beta 1. In this dataset, we include the expression data obtained from A549 cells after treatment with purified flagellin or transforming growth factor beta 1 receptor. The analysis indicated that flagellin induced a change in gene expression that was similar to the changes induced by transforming growth factor 1. A549 cells were treated with flagellin or transforming growth factor 1 for 24 h. Total RNA was extracted and reverse transcribed to cDNA. Synthesized cDNA was fragmented and labeled with biotin. The biotinylated cDNA was hybridized to to an Affymetrix GeneChip Array, and probe signal intensities were captured.

2012-10-31 | E-GEOD-38309 | biostudies-arrayexpress

Expression data from bovine bone-marrow derived MSCs following preconditioning (hypoxia and/or transforming growth factor-beta (TGF-β))

Project description:The innate repair and regeneration potential of skeletal tissues such as the intervertebral disc and articular cartilage is extremely limited, in part due to their avascularity and low cell density. Despite recent advances in MSC-based disc and cartilage regeneration, key challenges remain, including the sensitivity of these cells to in vivo microenvironmental stress such as low oxygen and nutrient levels. The objective of this study was to investigate whether preconditioning with hypoxia and/or transforming growth factor-beta (TGF-β) can enhance MSC survival and extracellular matrix production in a low oxygen and nutrient-limited microenvironment. Secondarily, the effects of donor variability on the response of MSCs to preconditioning was examined. MSCs from multiple bovine donors were preconditioned in monolayer in normoxia or hypoxia, with or without TGF-β. The effects of preconditioning on MSC gene expression during monolayer expansion were examined using microarrays.

2019-01-01 | GSE109567 | GEO

TGF-Beta 3 heterozygous mice

Project description:Transforming growth factor β (TGFβ) family comprises the main player in the development of fibrosis including three isoforms: TGFβ1, TGFβ2 and TGFβ3. TGFβ3 may play an antifibrotic role at the renal level, counteracting the role of TGFβ1, using a mouse model heterozygous for the TGFβ3 gene (TGFβ3+/-). Partial deletion of TGFβ3 causes in the mice albuminuria, loss of glomerular filtration rate, accelerated fibrosis, epithelial-to-mesenchymal transition and increment of glomerular basement membrane thickening.

2019-12-19 | ST001303 | MetabolomicsWorkbench

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