E-GEOD-35332
Ontology highlight
ABSTRACT:
OTHER RELATED OMICS DATASETS IN: PRJNA152645
PROVIDER: E-GEOD-35332 | ExpressionAtlas | 2014-07-03
REPOSITORIES: ExpressionAtlas
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| E-GEOD-35332-analysis-methods.tsv | Tabular | |||
| E-GEOD-35332-atlasExperimentSummary.Rdata | Rdata | |||
| E-GEOD-35332-configuration.xml | Xml | |||
| E-GEOD-35332-percentile-ranks.tsv | Tabular | |||
| E-GEOD-35332.condensed-sdrf.tsv | Tabular |
Items per page: 5 1 - 5 of 84 |
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Project description:Elevated mitochondrial biogenesis and metabolism represent key features of breast cancer stem cells (CSCs), whose propagation is conducive to disease onset and progression. Therefore, interfering with mitochondria biology and function may be regarded as a useful approach to eradicate CSCs. Here, we used the breast cancer cell line MCF7 as a model system to interrogate how mitochondrial fission contributes to the development of mitochondrial dysfunction toward the inhibition of metabolic flux and stemness. We generated an isogenic MCF-7 cell line transduced with Mitochondrial Fission Factor (MCF7-MFF), which is primarily involved in mitochondrial fission. We evaluated the biochemical, molecular and functional properties of MCF7-MFF cells, as compared to control MCF7 cells transduced with the empty vector (MCF7-Control). We observed that MFF over-expression reduces both mitochondrial mass and activity, as evaluated using the mitochondrial probes MitroTracker Red and MitoTracker Orange, respectively. The analysis of metabolic flux using the Seahorse XFe96 revealed the inhibition of OXPHOS and glycolysis in MCF7-MFF cells, suggesting that increased mitochondrial fission may impair the biochemical properties of these organelles. Notably, CSCs activity, assessed by 3D-tumorsphere assays, was reduced in MCF7-MFF cells. A similar trend was observed for the activity of ALDH, a well-established marker of stemness. We conclude that enhanced mitochondrial fission may compromise CSCs propagation, through the impairment of mitochondrial function, possibly leading to a quiescent cell phenotype. Unbiased proteomic analysis revealed that proteins involved in mitochondrial dysfunction, oxidative stress-response, fatty acid metabolism and hypoxia signaling are among the most highly up-regulated in MCF7-MFF cells. Of note, integrated analysis of top regulatory networks obtained from unbiased proteomics in MCF7-MFF cells predicts that this cell phenotype activates signaling systems and effectors involved in the inhibition of cell survival and adhesion, together with the activation of specific breast cancer cell death programs. Overall, our study shows that unbalanced and abnormal activation of mitochondrial fission may drive the impairment of mitochondrial metabolic function, leading to inhibition of CSC propagation, and the activation of quiescence programs. Exploiting the potential of mitochondria to control pivotal events in tumor biology may, therefore, represent a useful tool to prevent disease progression.
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Project description:Hamey2017 - Blood stem cell regulatory
network
This model is described in the article:
Reconstructing blood stem
cell regulatory network models from single-cell molecular
profiles
Fiona K. Hamey, Sonia Nestorowa,
Sarah J. Kinston, David G. Kent, Nicola K. Wilson, and Berthold
Göttgens
Proceedings of the National Academy of
Sciences of the United States of America
Abstract:
Adult blood contains a mixture of mature cell types, each
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single-cell snapshot expression data based on expression
profiles of 48 genes in 2,167 blood stem and progenitor cells.
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network models that recapitulated differentiation of HSCs into
progenitor cell types, focusing on trajectories toward
megakaryocyte–erythrocyte progenitors and lymphoid-primed
multipotent progenitors. By comparing these two models, we
identified and subsequently experimentally validated a
difference in the regulation of nuclear factor, erythroid 2
(Nfe2) and core-binding factor, runt domain, alpha subunit 2,
translocated to, 3 homolog (Cbfa2t3h) by the transcription
factor Gata2. Our approach confirms known aspects of
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biological systems to uncover regulatory relationships.
This model is hosted on
BioModels Database
and identified by:
MODEL1610060000.
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.
2017-06-09 | MODEL1610060000 | BioModels
Project description:Hamey2017 - Blood stem cell regulatory
network (LMPP network)
This model is described in the article:
Reconstructing blood stem
cell regulatory network models from single-cell molecular
profiles
Fiona K. Hamey, Sonia Nestorowa,
Sarah J. Kinston, David G. Kent, Nicola K. Wilson, and Berthold
Göttgens
Proceedings of the National Academy of
Sciences of the United States of America
Abstract:
Adult blood contains a mixture of mature cell types, each
with specialized functions. Single hematopoietic stem cells
(HSCs) have been functionally shown to generate all mature cell
types for the lifetime of the organism. Differentiation of HSCs
toward alternative lineages must be balanced at the population
level by the fate decisions made by individual cells.
Transcription factors play a key role in regulating these
decisions and operate within organized regulatory programs that
can be modeled as transcriptional regulatory networks. As
dysregulation of single HSC fate decisions is linked to fatal
malignancies such as leukemia, it is important to understand
how these decisions are controlled on a cell-by-cell basis.
Here we developed and applied a network inference method,
exploiting the ability to infer dynamic information from
single-cell snapshot expression data based on expression
profiles of 48 genes in 2,167 blood stem and progenitor cells.
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network models that recapitulated differentiation of HSCs into
progenitor cell types, focusing on trajectories toward
megakaryocyte–erythrocyte progenitors and lymphoid-primed
multipotent progenitors. By comparing these two models, we
identified and subsequently experimentally validated a
difference in the regulation of nuclear factor, erythroid 2
(Nfe2) and core-binding factor, runt domain, alpha subunit 2,
translocated to, 3 homolog (Cbfa2t3h) by the transcription
factor Gata2. Our approach confirms known aspects of
hematopoiesis, provides hypotheses about regulation of HSC
differentiation, and is widely applicable to other hierarchical
biological systems to uncover regulatory relationships.
This model is hosted on
BioModels Database
and identified by:
MODEL1610060001.
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.
2017-06-09 | MODEL1610060001 | BioModels
Project description:<p>Non-coding elements in our genomes that play critical roles in complex disease are frequently marked by highly unstable RNA species. Sequencing nascent RNAs attached to an actively transcribing RNA polymerase complex can identify unstable RNAs, including those templated from gene-distal enhancers (eRNAs). However, nascent RNA sequencing techniques remain challenging to apply in some cell lines and especially to intact tissues, limiting broad applications in fields such as cancer genomics and personalized medicine. Here we report the development of chromatin run-on and sequencing (ChRO-seq), a novel run-on technology that maps the location of RNA polymerase using virtually any frozen tissue sample, including samples with degraded RNA that are intractable to conventional RNA-seq. We used ChRO-seq to develop the first maps of nascent transcription in 23 human glioblastoma (GBM) brain tumors and patient derived xenografts. Remarkably, >90,000 distal enhancers discovered using the signature of eRNA biogenesis within primary GBMs closely resemble those found in the normal human brain, and diverge substantially from GBM cell models. Despite extensive overall similarity, 12% of enhancers in each GBM distinguish normal and malignant brain tissue. These enhancers drive regulatory programs similar to the developing nervous system and are enriched for transcription factor binding sites that specify a stem-like cell fate. These results demonstrate that GBMs largely retain the enhancer landscape associated with their tissue of origin, but selectively adopt regulatory programs that are responsible for driving stem-like cell properties. We also identified enhancers and their associated transcription factors that regulate genes characteristic of each known GBM subtype, and discovered a core group of transcription factors that control the expression of genes associated with clinical outcomes. This study uncovers new insights into the molecular etiology of GBM and introduces ChRO-seq which can now be used to map regulatory programs contributing to a variety of complex diseases.</p>
| phs001646 | dbGaP
Project description:T cell development is accompanied by epigenetic changes that ensure the silencing of stem cell-related, and the activation of lymphocyte-specific programs. How transcription factors influence these changes remains unclear. We show that the Ikaros transcription factor interacts with the Polycomb Repressive Complex 2 (PRC2) in CD4-CD8- thymocytes, and allows its binding to >200 developmentally-regulated genes, many of which are expressed in hematopoietic stem cells. Loss of Ikaros in CD4-CD8- cells leads to diminished histone H3 Lys27 (H3K27) trimethylation and ectopic expression of these genes. Ikaros binding triggers PRC2 recruitment and H3K27 trimethylation. Furthermore, Ikaros interacts with PRC2 independently of the Nucleosome Remodeling and Deacetylation complex. Our results identify Ikaros as a fundamental regulator of PRC2 function in developing T cells. Genome-wide comparison of different histone modifications, Ikaros, Suz12 and NuRD binding in different stages of T cell development in WT and Ikaros mutant mice. Profiling of H3K27me3 in DN1, DN2, DN3, DN4 and DP thymocytes and hematopoietic stem and progenitor cells (LSK cells) of WT and Ikaros mutant mice. Profiling of H3K4me3 and H3ac in WT and Ikaros mutant DP thymocytes. Global analysis of Ikaros binding in WT DN3, DN4 and DP cells, Suz12 binding in WT and Ikaros mutant DN3 cells, and Mta2 and Mi2beta binding in WT DN3 cells. Genome-wide profiling of Ikaros binding and H3K27me3 upon Ikaros activation in Ikaros-deficient leukemic T cells.
2015-11-03 | E-GEOD-61148 | biostudies-arrayexpress