Browse
Submit Data
Databases
API
Help

Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

40 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single-cell RNA-seq of Ecad positive PyMT bulk tumor cells

ABSTRACT: In this study we studied the presence of tumor cells that underwent epithelial-to-mesenchymal transition within polyoma middle T antigen (PyMT) breast tumors. For this we dissociated tumors and isolated Ecad positive tumor cells by FACS sorting. We confirmed that PyMT tumors contain a small set of tumor cells that have undergone EMT in the primary tumor and that E-cadherin can be used as a marker on single cell level for mesenchymal status in this model. We isolated primary tumors from mice, dissociated the tumors and FACS-sorted for single Ecad positive tumor cells, after this we performed single cell sequencing of the cells.

ORGANISM(S): Mus musculus

SUBMITTER: Jean-Charles Boisset

PROVIDER: E-GEOD-77107 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Json Xml

Publications

Plasticity between Epithelial and Mesenchymal States Unlinks EMT from Metastasis-Enhancing Stem Cell Capacity.

Beerling Evelyne E Seinstra Daniëlle D de Wit Elzo E Kester Lennart L van der Velden Daphne D Maynard Carrie C Schäfer Ronny R van Diest Paul P Voest Emile E van Oudenaarden Alexander A Vrisekoop Nienke N van Rheenen Jacco J

Cell reports 20160303 10

Forced overexpression and/or downregulation of proteins regulating epithelial-to-mesenchymal transition (EMT) has been reported to alter metastasis by changing migration and stem cell capacity of tumor cells. However, these manipulations artificially keep cells in fixed states, while in vivo cells may adapt transient and reversible states. Here, we have tested the existence and role of epithelial-mesenchymal plasticity in metastasis of mammary tumors without artificially modifying EMT regulators ...[more]

PMID: 26947068

Similar Datasets

A single-cell transcriptome atlas of the human pancreas

Project description:To understand organ (dys)function it is important to have a complete inventory of its cell types and the corresponding markers that unambiguously identify these cell types. This is a challenging task, in particular in human tissues, because unique cell-type markers are typically unavailable, necessitating the analysis of complex cell type mixtures. Transcriptome-wide studies on pancreatic tissue are typically done on pooled islet material. To overcome this challenge we sequenced the transcriptome of thousands of single pancreatic cells from deceased organ donors with and without type 2 diabetes (T2D) allowing in silico purification of the different cell types. We identified the major pancreatic cell types resulting in the identification of many new cell-type specific and T2D-specific markers. Additionally we observed several subpopulations within the canonical pancreatic cell types, which we validated in situ. This resource will be useful for developing a deeper understanding of pancreatic biology and diabetes mellitus. Human cadaveric pancreata were used to extract islets of Langerhans, which were kept in culture until single-cell dispersion and FACS sorting. Single-cell transcriptomics was performed on live cells from this mixture using CEL-seq or on cells stained for CD63, CD13, TGFBR3 or CD24 and CD44. The RaceID algorithm was used to identify clusters of cells corresponding to the major pancreatic cell types and to mine for novel cell type-specific genes as well as subpopulations within the known pancreatic cell types.

2016-06-24 | E-GEOD-81076 | biostudies-arrayexpress

Single-cell RNA-seq of sorted and micro-dissected mouse bone marrow cells

Project description:We here systematically studied the interaction network of bone marrow cells. To this end, we micro-dissected many small interacting structures (cell doublets, triplets etc.) into single cells, and sequenced their mRNAs, to infer cell identity. After grouping the cells into cell types (based on the single-cell transcriptomes), we identified actual physical interactions that occurred more, or less, than what would be expected by chance. We compared the micro-dissected data to sorted hematopoietic stem cells. After mild dissociation of the bone marrow, we micro-dissected many small interacting structures (cell doublets, triplets etc.) into single cells, and sequenced their mRNAs. In addition, single hematopoietic stem cells were sorted (Lineage- Kit+ Sca1+ CD150+ CD48-) to sequence their transcriptome. In detail, the bone marrow was mildly flushed. Structures composed of about 10 to 20 cells were set apart. With needles and a micro-dissection microscope, we trimmed of smaller structures from these big structure. These smaller structures are mainly two to four cells attached together. These small structures were then further micro-dissected to single cells. The goal of doing these sequential dissections was to keep track of which cells were interacting with which. Each micro-dissected cell sample contains RNA-seq data for 96 single cells. Each single cells received a different barcode that allow us to entangle them, and to produce the processed .coutt.csv file. Each sorted hematopoietic stem cell sample represents a single cell. The processed data file expdata_BMJhscC.csv contains transcript counts for all analyzed cells.

2016-06-24 | E-GEOD-76983 | biostudies-arrayexpress

Validation of noise models for single-cell transcriptomics

Project description:Single-cell transcriptomics has recently emerged as a powerful technology to explore gene expression heterogeneity amongst single cells. Here we identify two major sources of technical variability, sampling noise and global cell-to-cell variation in sequencing efficiency. We propose noise models to correct for this and after validation by single-molecule FISH experiments, we apply these models to demonstrate that growing mES cells in 2i instead of serum/LIF globally reduces gene expression variability. J1 mouse embryonic stem cells (mESCs) were cutured in 2i or in serum medium. Cells were dissociated into a single cell suspension and picked under a stereomicroscope using a 30Î¼m glass capillary and mouth pipette. Picked cells were deposited in the lid of an 0.5ml LoBind eppendorf tube and snap frozen in liquid nitrogen. For the pool and split controls, approximately 1 million cells were lysed, the amount of RNA was quantified on a bioanalyzer (Agilent) using the Eukaryote Total RNA pico kit. 20pg aliquots of total RNA were used for each pool and split control. Single cells and controls were processed using the previously described CEL-seq technique, with a few alterations. A 4bp random barcode as unique molecular identifier (UMI) was added to the primer in between the cell specific barcode and the poly T stretch. Libraries were sequenced on an Illumina HighSeq 2500 using 50bp paired end sequencing. For cells and controls, two libraries were sequenced on two lanes in total for each condition.

2014-04-20 | E-GEOD-54695 | biostudies-arrayexpress

Plasticity between Epithelial and Mesenchymal States Unlinks EMT from Metastasis-Enhancing Stem Cell Capacity

Project description:In this study we studied the presence of tumor cells that underwent epithelial-to-mesenchymal transition within polyoma middle T antigen (PyMT) breast tumors. For this we dissociated tumors and isolated Ecad positive tumor cells by FACS sorting. We confirmed that PyMT tumors contain a small set of tumor cells that have undergone EMT in the primary tumor and that E-cadherin can be used as a marker on single cell level for mesenchymal status in this model.

2016-03-09 | GSE77107 | GEO

RNA-seq gene expression of flow cytometry sorted breast cancer stem cell populations

Project description:MMTV-PyMT transgenic FVBN mice spontaneously developed breast tumors. Two tumors were collected as replicate samples, and cells from the dissociated tissue were sorted into 2 cancer stem cell (CSC) populations, along with the remaining non-CSCs. The samples were submitted for RNAseq to generate differential gene expression profiles of the breast tumor CSC populations.

2021-11-21 | GSE189223 | GEO

Consequences of sEH deletion in the polyoma middle T (PyMT) breast cancer tumor proteome

Project description:The aim of this investigation was to study the consequences of interfering with soluble epoxide hydrolase (sEH) expression on tumor growth and metastasis in genetically modified animals that spontaneously generate tumors without the exogenous application of high concentrations of epoxide mediators or inhibitors. Therefore, breast cancer development was studied in mice expressing the polyoma middle T oncogene (PyMT) under the control of the mouse mammary tumor virus promoter, to induce spontaneous mammary tumors. To facilitate the study of endogenous sEH activity in tumor growth, PyMT mice were then crossed with sEH-/- mice to generate sEH-deficient mice that spontaneously generate breast tumors (so called PyMTsEH mice). For these analyses, primary tumors were removed from 20 week old mice.

2021-09-14 | PXD026214 | Pride

Effect of Spot14 Loss on Gene Expression Profile of MMTV-PyMT Mouse Tumors

Project description:The objective of this study was to determine the effect of Thyroid Hormone Responsive Protein Spot14 (Spot14) loss on the gene expression profiles of tumors from MMTV-Polyomavirus middle-T antigen (PyMT) mice. MMTV-PyMT/S14-heterozygous mice were crossed with S14-heterozygous mice and 1 cm tumors from MMTV-PyMT control (wild-type S14) or MMTV-PyMT/S14-null offspring were profiled using Affymetrix gene arrays. Tumor latency was not different between groups; however, tumors lacking S14 grew significantly slower than control tumors. Loss of S14 also decreased the levels of de novo synthesized fatty acids in mammary tumors. In additional studies, performed on MMTV-Neu mice, we found that S14 overexpression was associated with increased tumor cell proliferation and elevated levels of tumor fatty acids. Gene expression profiling revealed that S14 loss and overexpression in mouse mammary tumors altered pathways associated with proliferation and metabolism. This study provides important information about the role of S14 in mammary tumorigenesis and tumor metabolism. Microarray analysis was performed on 4 mammary tumors from MMTV-PyMT mice and 4 tumors from MMTV-PyMT/S14-null mice.

2014-09-01 | E-GEOD-55886 | biostudies-arrayexpress

Gene expression of polyoma middle T antigen induced mammary tumors

Project description:This SuperSeries is composed of the following subset Series: GSE30864: Gene expression of polyoma middle T antigen induced mammary tumors [AKXD x PyMT] GSE30865: Gene expression of polyoma middle T antigen induced mammary tumors [NZB x PyMT] GSE31223: Gene expression of polyoma middle T antigen induced mammary tumors [RNA_Seq : MOLF x PyMT] Refer to individual Series

2011-07-21 | E-GEOD-30866 | biostudies-arrayexpress

Effect of Spot14 Loss on Gene Expression Profile of MMTV-PyMT Mouse Tumors

2014-09-01 | GSE55886 | GEO

Differential expression of GFP+ and RFP+ TriPyMT cells

Project description:Tri-PyMT cell is a breast tumor cell line established from Tri-PyMT (MMTV-PyMT/fsp1-Cre/Rosa26-RGFP) primary breast tumors. The cells switch from RFP+ to GFP+ during epithelial to mesenchymal transition (EMT). Differential expressed genes between EMT and non-EMT tumor cells will reveal interesting targets for anti-EMT approaches.

2015-09-01 | GSE72480 | GEO

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