Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Regulation of cellular heterogeneity and symmetric/asymmetric divisions in triple-negative breast cancer

PROVIDER: PRJNA477728 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR7418760.fastq.gz	Fastqsanger.gz
	SRR7418760_1.fastq.gz	Fastqsanger.gz
	SRR7418760_2.fastq.gz	Fastqsanger.gz
	SRR7418761.fastq.gz	Fastqsanger.gz
	SRR7418761_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 10

Similar Datasets

Regulation of cellular heterogeneity and rates of symmetric and asymmetric divisions in triple-negative breast cancer

Project description:Regulation of cellular heterogeneity and rates of symmetric and asymmetric divisions in triple-negative breast cancer

| PRJNA328149 | ENA

Regulators of cellular heterogeneity in basal-like breast cancer influence symmetric versus asymmetric division rates (shRNA targeting)

Project description:Differentiation events contribute to cellular heterogeneity within tumors and influence disease progression and response to therapy. Here we dissect the mechanisms controlling intratumoral heterogeneity within basal-like breast cancers. We show that cancer cells can transition between a differentiation state related to that of normal luminal progenitors and a state closer to that of mature luminal cells, and that this occurs through asymmetric cell divisions. The Polycomb factor EZH2 and the Notch pathway act to increase the rates of symmetric divisions that produce progenitor-like cells, while the FOXA1 transcription factor promotes asymmetric divisions that reduce the numbers of such cells. Through functional screening, we identified a group of regulators that control cancer cell differentiation state and the relative proportions of tumor cell subpopulations. Our findings highlight the regulation of asymmetric cell divisions as a mechanism controlling intratumoral heterogeneity, and identify molecular pathways that control breast cancer cellular composition.

2018-08-26 | GSE84143 | GEO

Regulators of cellular heterogeneity in basal-like breast cancer influence symmetric versus asymmetric division rates (Expression profiles)

2018-08-26 | GSE84080 | GEO

Homo sapiens

Project description:Heterogeneity of triple-negative breast cancer

| PRJNA381463 | ENA

RNA methylation maintains hematopoietic stem cell identity and symmetric commitment

Project description:Stem cells balance cellular fates through asymmetric and symmetric divisions in order to self-renew or to generate downstream progenitors. Symmetric commitment divisions in stem cells are required for rapid regeneration during tissue damage and stress. The control of symmetric commitment remains poorly defined. N6-methyladenosine (m6A), the most abundant posttranscriptional mRNA modification controls cellular states and its abundance is dysregulated in cancer. Here we show that mRNA methylation controls symmetric commitment and cell identity of hematopoietic stem cells (HSCs). Using single-cell RNA sequencing (scRNA-seq) in combination with transcriptomic profiling of HSPCs (hematopoietic stem and progenitor cells) from control and m6A methyltransferase Mettl3 conditional knockout mice, we found that m6A-deficient HSC fail to symmetrically differentiate. Dividing HSCs are expanded and are blocked in an intermediate state that molecularly and functionally resembles multipotent progenitors. Mechanistically, RNA methylation controls Myc mRNA abundance in differentiating HSCs. Importantly, we identified MYC as a new marker for HSC asymmetric and symmetric commitment. Furthermore, forced expression of MYC rescued m6A’s requirement for engraftment indicating its importance in the early stage of HSC cellular fate. Overall our results indicate that RNA methylation is critical for normal blood homeostasis and may provide a general mechanism for how stem cells regulate differentiation fate choice.

2019-07-25 | GSE132357 | GEO

Homo sapiens

Project description:Regulators of cellular heterogeneity in basal-like breast cancer influence symmetric versus asymmetric division rates (Expression profiles)

| PRJNA327998 | ENA

Homo sapiens

Project description:Regulators of cellular heterogeneity in basal-like breast cancer influence symmetric versus asymmetric division rates (shRNA targeting)

| PRJNA328143 | ENA

Heterogeneity of triple-negative breast cancer

Project description:Heterogeneity of triple-negative breast cancer was examined and compared across morphologic and molecular features

2018-01-01 | GSE97342 | GEO

Decoding gene expression heterogeneity in Triple Negative Breast Cancer

Project description:Decoding gene expression heterogeneity in Triple Negative Breast Cancer

| PRJNA1106798 | ENA

Asymmetric cancer cell division regulated by AKT, Reactive Oxygen Species (ROS) high versus ROS low mRNA

Project description:Human tumors often contain slowly proliferating cancer cells that resist treatment but we do not know precisely how these cells arise. We show that rapidly proliferating cancer cells can divide asymmetrically to produce slowly proliferating “G0-like” progeny that are enriched following chemotherapy in breast cancer patients. Asymmetric cancer cell division results from asymmetric suppression of AKT/PKB kinase signaling in one daughter cell during telophase of mitosis. Moreover, inhibition of AKT signaling with small molecule drugs can induce asymmetric cancer cell division and the production of slow proliferators. Cancer cells therefore appear to continuously flux between symmetric and asymmetric division depending on the precise state of their AKT signaling network. This model may have significant implications for understanding how tumors grow, evade treatment, and recur. 3 replicates each of MCF7 Reactive Oxygen Species (ROS) high, HCT116 ROS high, MCF7 ROS low, and HCT116 ROS low.

2011-07-14 | E-GEOD-30465 | 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