Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Distinct epigenetic profiles at the cytosine modification level define epithelial-to-mesenchymal cell-state transitions

ABSTRACT: Genome wide DNA methylation and hydroxymethylation profiling of 6 isolated single cell clones and the parental (SUM149-PT) cell line. The Illumina Infinium Human MethylationEPIC Beadchip was used to obtain DNA methylation and hydroxymethylation profiles across approximately 850,000 CpGs in 6 isolated single cell clones that represent the phenotypes of the epithelial-to-mesenchymal spectrum along with the parental (SUM149-PT) cell line. Isolated single cell clones represent varying phenotypes of the epithelial-to-mesenchymal transition. Detailed isolation and characterization methods can be found in Brown et al, 2021. https://doi.org/10.1101/2021.03.17.434993

ORGANISM(S): Homo sapiens

PROVIDER: GSE181036 | GEO | 2022/05/27

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

aCGH: Human SUM149-Luc triple-negative Inflammatory Breast Cancer cell line versus its metabolically adaptable variants MA1 and MA2

Project description:CGH array of MA1 and MA2 variant cells as compared to the parental SUM149-Luc breast cancer cell line. The MA1 and MA2 variants were isolated based on the ability of rare cancer cells to survive and grow without adding glutamine in culture medium. To gain insight into the characteristic of metabolically adaptable MA cells that enables them to survive severe metabolic challenge, i.e., prolonged lack of glutamine and other challenges [Singh et al., PLoS ONE 7: e36510, 2012], we analyzed CGH array to compare these cells with the parental SUM149-Luc (luciferase-transfected) cells. We analyzed two independently selected cell populations, one from 0.5 million parental cells (designated MA1) and one from 1 million parental cells (designated MA2).

2014-10-03 | GSE60015 | GEO

aCGH: Human SUM149-Luc triple-negative Inflammatory Breast Cancer cell line versus its metabolically adaptable variants MA1 and MA2

2014-10-03 | E-GEOD-60015 | biostudies-arrayexpress

Bortezomib resistance in Mantle Cell Lymphoma (MCL) is associated with plasmacytic differentiation

Project description:Bortezomib-induced resistant MCL cell lines (HBL2 BR and JEKO BR) were generated by continuous cultured of corresponding parental cell lines (HBL2 PT and JEKO PT) with increasing bortezomib concentrations The IC50 of bortezomib of BR cell lines was 80 fold higher than the IC50 of the parental clone for HBL2-BR and 40 fold higher for JEKO-BR.RNA was isolated from cells collected at different time points within the period of one month in triplicate for HBL2 and in duplicate for JEKO subclones. This material was used for gene expression analysis using Affymetrix platform. Keywords: RNA Comparision of gene expression profiling in matched pairs of PT and BR cell lines

2010-10-13 | E-GEOD-20915 | biostudies-arrayexpress

Gene expression of metabolically adaptable triple-negative breast cancer cells

Project description:To gain insight into the characteristic of metabolically adaptable MA cells that enables them to survive severe metabolic challenge, i.e., prolonged lack of glutamine and other challenges [Singh et al., PLoS ONE 7: e36510, 2012], we used gene expression microarrays to compare these cells with the parental SUM149-Luc (luciferase-transfected) cells. We analyzed two independently selected cell populations, one from 0.5 million parental cells (designated MA1) and one from 1 million parental cells (designated MA2). Comparing MA1 and MA2 variants to a common parental cell line SUM149-Luc. One sample each.

2014-10-03 | E-GEOD-60016 | biostudies-arrayexpress

Bortezomib resistance in Mantle Cell Lymphoma (MCL) is associated with plasmacytic differentiation

2010-10-13 | GSE20915 | GEO

Multinucleated Tartrate Resistant Acid Phosphatase Positive Cells with Macrophage and Osteoclast Phenotypes in Bone

Project description:Prothrombin (PT) and osteopontin (OPN) promotes adhesion of different TRAP-positive multinucleated cells isolated from rat long bone (Hu et al. Exp Cell Res. 2008; 314: 638-50). The PT-adhering cell could represent either an immature precursor to the OPN-adherent osteoclast or constitute a distinct multinucleated cell population with a unique role in bone. Herein, phenotypic differences between PT- and OPN- cells were investigated with microarray- expression analysis. Characteristic for PT-cells was expression of innate immune response genes and scavenger receptors whereas OPN-cells expressed typical osteoclast proteins such as collagenases implicated in bone degradation.

2010-12-31 | GSE19950 | GEO

Multinucleated Tartrate Resistant Acid Phosphatase Positive Cells with Macrophage and Osteoclast Phenotypes in Bone

2010-12-31 | E-GEOD-19950 | biostudies-arrayexpress

Single cell RNA-seq of bioprinted human kidney organoid

Project description:These files represent single cell RNA-Seq data generated on a 10x Chromium genomics platform from bioprinted iPSC-derived human kidney organoids differentiated according to our published protocol (Takasato et al., Nature Protocols 2016). The data contains >2000 cells that passed our QC. Data was used to confirm that bioprinted organoids contain a similar cellular composition as standard manually produced organoids - See https://www.biorxiv.org/content/10.1101/505396v1.

2020-09-01 | GSE138835 | GEO

Single cell RNA trajectory analysis reveals a CD9 positive cell state to contribute to exit from stem cell-like and embryonic diapause states and transit to drug resistant states

Project description:Bromo- and extra-terminal domain (BET) inhibitors (BETi) have been shown to decrease tumor growth in preclinical models and clinical trials. However, toxicity and rapid emergence of resistance have limited their clinical implementation. To identify state changes underlying acquisition of resistance to the JQ1 BETi, we reanalyzed single-cell RNAseq data from JQ1 sensitive and resistant SUM149 and SUM159 triple negative breast cancer cell lines. Parental and JQ1-resistant SUM149 and SUM159 exhibited a stem cell-like and embryonic diapause (SCLED) cell state as well as a transitional cell state between the SCLED state existing both treatment naïve and treated cells, and a number of JQ1 resistant cell states. A transitional cell state transcriptional signature but not a SCLED state transcriptional signature predicted worsened outcomes in basal-like breast cancer patients suggesting that transit from the SCLED state to drug resistant states contributes to patient outcomes. Entry of SUM149 and SUM159 into the transitional cell state was characterized by elevated expression of the CD9 tetraspanin. Knockdown or inhibition of CD9 sensitized cells to multiple targeted and cytotoxic drugs in vitro. Importantly, CD9 knockdown or blockade sensitized SUM149 to JQ1 in vivo by trapping cells in the SCLED state and limiting transit to resistant cell states. Thus, CD9 appears to be critical for transition from a SCLED state into treatment resistant cell states and warrants exploration as a therapeutic target in basal-like breast cancer.

2023-06-01 | GSE221183 | GEO

Expression data from melanoma subpopulations

Project description:We aimed at identifying lymphangiogenic subpopulations by comparative analysis of single cell clones derived from a melanoma of a single patient. Selected clones were grafted into SCID mice, where they induced lymphangiogenesis and metastasized into sentinel nodes, whereas non-lymphangiogenic clones from the same patient did not metastasize. RNA isolated from primary SCID mouse tumors were used for transcriptome analysis. A total of 16 Samples were analysed, 4 per group. Parental pool MCM1(C), nonlymphangiogenic MCM1G(G), lymphangiogenic MCM1D(D1), lymphangiogenic and very metastatic MCM1DLN(D2).

2012-06-17 | E-GEOD-36035 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data