Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Unveiling the differential Senescence Phenotypes of MCF7 Cells Treated with Diverse Therapeutic Agents: A Comprehensive Transcriptome Analysis

ABSTRACT: Therapeutic drugs are commonly used for treatment various cancers. However, despite to this purpose, Cancer treated by drugs undergoes senescence phenotypes and is known to acquire more aggressive ability. Futhermore, senescence can be induced vairous type of drug via differential mechanisms. Therefore, we analyzed to validate differential charateristics of senescence phenotypes compare between drugs.

ORGANISM(S): Homo sapiens

PROVIDER: GSE229264 | GEO | 2023/04/14

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Unveiling the differential Senescence Phenotypes of MCF7 Cells Treated with Diverse Therapeutic Agents: A Comprehensive Transcriptome Analysis

Project description:Unveiling the differential Senescence Phenotypes of MCF7 Cells Treated with Diverse Therapeutic Agents: A Comprehensive Transcriptome Analysis

| PRJNA953769 | ENA

Senescence-induced endothelial phenotypes underpin immune-mediated senescence surveillance

Project description:Senescence-induced endothelial phenotypes underpin immune-mediated senescence surveillance

| PRJNA801491 | ENA

Heterozygous variants in POLR1A cause diverse human phenotypes

Project description:Heterozygous variants in POLR1A cause diverse human phenotypes

| PRJNA849583 | ENA

Implications of time-series gene expression profiles of replicative senescence

Project description:Although senescence has long been implicated in aging-associated pathologies, it is not clearly understood how senescent cells are linked to these diseases. To address this knowledge gap, we profiled cellular senescence phenotypes and mRNA expression patterns during replicative senescence in human diploid fibroblasts. We identified a sequential order of gain-of-senescence phenotypes: low levels of reactive oxygen species, cell mass/size increases with delayed cell growth, high levels of reactive oxygen species with increases in senescence-associated M-NM-2-galactosidase activity (SA-M-NM-2-gal), and high levels of SA-M-NM-2-gal activity. Gene expression profiling revealed four distinct modules in which genes were prominently expressed at certain stages of senescence, allowing us to divide the process into four stages: early, middle, advanced, and very advanced. Interestingly, the gene expression modules governing each stage supported the development of the associated senescence phenotypes. Senescence-associated secretory phenotype-related genes also displayed a stage-specific expression pattern with three unique features during senescence: differential expression of interleukin isoforms, differential expression of interleukins and their receptors, and differential expression of matrix metalloproteinases and their inhibitory proteins. The analysis of time series gene expression level during replicaive senescence.

2013-04-24 | E-GEOD-41714 | biostudies-arrayexpress

IMMUNE SENESCENCE PHENOTYPES PREDICT CHEMOTHERAPY RESISTANCE IN ACUTE MYELOID LEUKAEMIA

Project description:IMMUNE SENESCENCE PHENOTYPES PREDICT CHEMOTHERAPY RESISTANCE IN ACUTE MYELOID LEUKAEMIA

| PRJNA734922 | ENA

Implications of time-series gene expression profiles of replicative senescence

Project description:Although senescence has long been implicated in aging-associated pathologies, it is not clearly understood how senescent cells are linked to these diseases. To address this knowledge gap, we profiled cellular senescence phenotypes and mRNA expression patterns during replicative senescence in human diploid fibroblasts. We identified a sequential order of gain-of-senescence phenotypes: low levels of reactive oxygen species, cell mass/size increases with delayed cell growth, high levels of reactive oxygen species with increases in senescence-associated β-galactosidase activity (SA-β-gal), and high levels of SA-β-gal activity. Gene expression profiling revealed four distinct modules in which genes were prominently expressed at certain stages of senescence, allowing us to divide the process into four stages: early, middle, advanced, and very advanced. Interestingly, the gene expression modules governing each stage supported the development of the associated senescence phenotypes. Senescence-associated secretory phenotype-related genes also displayed a stage-specific expression pattern with three unique features during senescence: differential expression of interleukin isoforms, differential expression of interleukins and their receptors, and differential expression of matrix metalloproteinases and their inhibitory proteins.

2013-04-24 | GSE41714 | GEO

Substrate Stiffness Dictates Unique Doxorubicin-induced Senescence-associated Secretory Phenotypes and Transcriptomic Signatures in Human Pulmonary Fibroblasts

Project description:Cells are subjected to dynamic mechanical environments which impart various forces and induce cellular responses. In age-related conditions like pulmonary fibrosis, there is both an increase in tissue stiffness and an accumulation of senescent cells, leading to elevated tension in fibroblasts among other cells. While senescent cells produce a senescence-associated secretory phenotype (SASP), the impact of physical stimuli on both cellular senescence and SASP is not well understood. Here, we show that mechanical tension, modeled using cell culture substrate rigidity, influences senescent cell markers like SA-beta-gal and secretory phenotypes. Comparing human primary pulmonary fibroblasts (IMR-90) cultured on physiological (2 kPa), fibrotic (50 kPa), and plastic (3 GPa) substrates followed by senescence induction using doxorubicin, we identified unique high-stiffness-driven secretory protein profiles using mass spectrometry and transcriptomic signatures, both showing an enrichment in collagen proteins. Computational meta-analysis of human interstitial lung disease single-cell RNA sequencing datasets confirmed these genes are highly expressed in disease samples and strongly correlate with mechanotransduction and senescence-related pathways. Thus, mechanical forces shape cell senescence and their secretory phenotypes.

| MSV000095880 | MassIVE

Single-Cell Map of Diverse Immune Phenotypes in Liver Microenvironment

Project description:Single-Cell Map of Diverse Immune Phenotypes in Liver Microenvironment

| PRJNA649917 | ENA

Transcriptome profile of Human Mesenchymal Stem Cells with Reduced Senescence and Increased Trilineage Differentiation Ability upon Drug Treatment

Project description:Human Mesenchymal stem cells (hMSCs) are multi-potential cells which are widely used in cell therapy. However, the frequently emerged senescence and decrease of differentiation capabilities limited the broad applications of MSC. In this study, hMSCs were treated by rapamycin, oltipraz, metformin, and vitamin C for the indicated time and the cells were subjected to senescence evaluation and trilineage differentiation. Transcriptomics dataset of hMSCs after drugs treatment was analyzed to interpret biological pathways responsible for the anti-senescence effects. Although four drugs exhibited significant activities in promoting MSC osteogenic differentiation, metformin is the optimal drug to promote trilineage differentiation. GO terms illustrated that the anti-aging effects of drugs were mainly associated with cellular senescence, mitotic and meiosis process. The method established and discussed in this study can be used to study different biological phenotypes upon drug intervention in MSC which will extend the clinical application of hMSCs.

2021-05-06 | GSE165201 | GEO

Epithelial phenotype restoring drugs suppress macular 1 degeneration phenotypes in an iPSC model

Project description:Epithelial phenotype restoring drugs suppress macular 1 degeneration phenotypes in an iPSC model

| PRJNA768489 | ENA