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Physiological glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts [EPIC]

ABSTRACT: Physiological glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts [EPIC]

PROVIDER: PRJNA865140 | ENA |

REPOSITORIES: ENA

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Physiological glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts [EPIC]

Project description:Chronic environmental stress can profoundly impact cell and body function. While the underlying mechanisms are poorly understood, epigenetics has emerged as a key link between environment and health. The genomic effects of stress are thought to be mediated by the action of glucocorticoid stress hormones, primarily cortisol in humans, which act via the glucocorticoid receptor (GR). To dissect how physiological GR activation influences epigenetic and cell states, human fibroblasts underwent prolonged exposure to physiological stress levels of cortisol and/or a selective GR antagonist. Cortisol was found to drive robust changes in cell proliferation, migration, and morphology, which were abrogated by concomitant GR blockade. These GR-driven phenotypes were accompanied by widespread, yet genomic context-dependent, changes in DNA methylation and mRNA expression involving genes with known roles in cell proliferation and migration. These findings provide novel insights into how chronic stress-driven functional epigenomic patterns become established to shape key cell phenotypes.

2022-08-15 | GSE210301 | GEO

Physiological glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts [TBS]

2022-08-15 | GSE210303 | GEO

Physiological glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts [RNA-seq]

2022-08-15 | GSE210302 | GEO

Physiological glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts [TBS]

Project description:Physiological glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts [TBS]

| PRJNA865138 | ENA

Physiological glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts [RNA-seq]

Project description:Physiological glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts [RNA-seq]

| PRJNA865139 | ENA

Chronic stress-driven glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts

Project description:Chronic stress-driven glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts

| PRJNA865136 | ENA

EPIC-HPS

Project description:EPIC-HPS

| PRJNA684138 | ENA

Chronic stress-driven glucocorticoid receptor activation programs key cell phenotypes and functional epigenomic patterns in human fibroblasts.

Project description:Chronic environmental stress can profoundly impact cell and body function. Although the underlying mechanisms are poorly understood, epigenetics has emerged as a key link between environment and health. The genomic effects of stress are thought to be mediated by the action of glucocorticoid stress hormones, primarily cortisol in humans, which act via the glucocorticoid receptor (GR). To dissect how chronic stress-driven GR activation influences epigenetic and cell states, human fibroblasts underwent prolonged exposure to physiological stress levels of cortisol and/or a selective GR antagonist. Cortisol was found to drive robust changes in cell proliferation, migration, and morphology, which were abrogated by concomitant GR blockade. The GR-driven cell phenotypes were accompanied by widespread, yet genomic context-dependent, changes in DNA methylation and mRNA expression, including gene loci with known roles in cell proliferation and migration. These findings provide insights into how chronic stress-driven functional epigenomic patterns become established to shape key cell phenotypes.

| S-EPMC9440308 | biostudies-literature

EPIC: Software Toolkit for Elution Profile-Based Inference of Protein Complexes

Project description:Heteromeric protein complexes are key macromolecular machines of the cell, but their description remains incomplete. We previously reported an experimental strategy for global characterization of native protein assemblies based on chromatographic fractionation of biological extracts coupled to precision mass spectrometry analysis (CF/MS), but the resulting data can be challenging to process and interpret. Here, we describe EPIC (Elution Profile-based Inference of Complexes), a software toolkit for automated scoring of CF/MS data for large-scale determination of high-confidence physical interaction networks and macromolecular assemblies from diverse biological specimens. As a case study, we used EPIC to map the global interactome of Caenorhabditis elegans, defining 590 putative worm protein complexes linked to diverse biological processes, including assemblies unique to nematodes. The EPIC software is freely available as a Jupyter notebook packaged in a Docker container (https://hub.docker.com/r/baderlab/bio-epic/), and the open source code is available via GitHub (https://github.com/BaderLab/EPIC).

2019-07-16 | PXD011182 | Pride

EPIC-Italy at HuGeF

Project description:This Series contains data from 845 participants (188 men and 657 women) in the EPIC-Italy cohort that was produced at the Human Genetics Foundation (HuGeF) in Turin, Italy. At the last follow-up (2010), 424 participants remained cancer-free, 235 had developed primary breast cancer, 166 had developed primary colorectal cancer, and 20 had developed other primary cancers. Anthropometric measurements, and dietary and lifestyle information obtained by questionnaire are also available. A total of 845 samples from the EPIC-Italy cohort were analyzed.

2013-09-20 | E-GEOD-51032 | biostudies-arrayexpress

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