Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq

ABSTRACT: Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq

PROVIDER: PRJNA485423 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq [WES]

Project description:Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq [WES]

| PRJNA485428 | ENA

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq [RNA-Seq]

Project description:Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq [RNA-Seq]

| PRJNA485429 | ENA

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq [WES]

Project description:Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by extensive intratumoral heterogeneity. To investigate the underlying biology, we conduct single-cell RNA- sequencing (scRNA-seq) of >1500 cells from six primary TNBC, together with whole exome sequencing (WES) for four of the tumors. Intercellular heterogeneity of gene expression programs within each tumor was variable and largely correlated with clonality of inferred genomic copy number changes, suggesting that genotype drives the gene expression phenotype of individual subpopulations. Clustering of gene expression profiles identified distinct subgroups of malignant cells shared by multiple tumors, including a single subpopulation associated with multiple signatures of treatment resistance and metastasis, and characterized functionally by activation of glycosphingolipid metabolism and associated innate immunity pathways. A novel signature defining this subpopulation was predictive of long-term outcomes for TNBC patients in a large patient cohort. Collectively, this analysis reveals the functional heterogeneity and its association with genomic evolution in TNBC, and uncovers unanticipated biological principles dictating poor outcomes in this disease.

2018-08-11 | GSE118303 | GEO

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq [RNA-Seq]

Project description:Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by extensive intratumoral heterogeneity. To investigate the underlying biology, we conduct single-cell RNA- sequencing (scRNA-seq) of >1500 cells from six primary TNBC. Intercellular heterogeneity of gene expression programs within each tumor was variable and largely correlated with clonality of inferred genomic copy number changes, suggesting that genotype drives the gene expression phenotype of individual subpopulations. Clustering of gene expression profiles identified distinct subgroups of malignant cells shared by multiple tumors, including a single subpopulation associated with multiple signatures of treatment resistance and metastasis, and characterized functionally by activation of glycosphingolipid metabolism and associated innate immunity pathways. A novel signature defining this subpopulation was predictive of long-term outcomes for TNBC patients in a large patient cohort. Collectively, this analysis reveals the functional heterogeneity and its association with genomic evolution in TNBC, and uncovers unanticipated biological principles dictating poor outcomes in this disease.

2018-08-11 | GSE118389 | GEO

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq.

Project description: Not available

| S-EPMC6123496 | biostudies-literature

Unravelling subclonal heterogeneity and aggressive disease states in TNBC through single-cell RNA-seq

Project description:This SuperSeries is composed of the SubSeries listed below.

2018-08-11 | GSE118390 | GEO

AR heterogeneity in TNBC MDA-MB-453 cells

Project description:Triple-negative breast cancer (TNBC) is aggressive and difficult, and few targeted therapies are available to treat this patient population. The androgen receptor (AR) has emerged as a potential target in breast cancer. Newer generation AR inhibitors, such as Seviteronel (Sevi), are unique in their ability to inhibit AR both directly and by blocking upstream androgen synthesis. The purpose of this study was to investigate the pre-clinical activity of Sevi in TNBC and further explore the effectiveness of targeting both androgen biosynthesis and AR activity in combination with other downstream acting agents. AR overexpressing (AR+) TNBC cell lines, xenografts and androgen responsive patient-derived xenograft (PDX) models were using to show how effectively Sevi inhibits AR activity and cell/tumor proliferation. Single cell RNA-sequencing of the AR+ cell line MDA-MB-453 illustrated heterogeneity in AR levels and identified cell cycle pathway activation in ARHigh versus ARLow expressing cells. Combination treatment with the cell cycle CDK4/6 inhibitor abemaciclib and Sevi showed synergy in AR+ TNBC cells and increased effectiveness, compared to each drug alone, in an AR+ TNBC xenograft model. While cell cycle inhibitors have been approved for use in hormone-receptor positive breast cancer, our studies suggest that these drugs may be equally effective in AR+ TNBC cells, especially when combined with AR antagonists. Implications. These data suggest that targeting AR signaling at multiple points throughout the pathway may be an effective was to treat patients with AR+ TNBC.

2020-06-12 | GSE152315 | GEO

Transcriptional heterogeneity among subclonal populations of MDA-MBA-468 triple-negative breast cancer cells

Project description:Intratumoral heterogeneity has been described for various tumor types and models of human cancer, and can have profound effects on tumor progression and drug resistance. This study describes transcriptional heterogeneity among subclonal populations (SCPs) derived from a single triple-negative breast cancer cell line.

2022-01-12 | GSE184540 | GEO

Transcriptional heterogeneity among xenograft tumors derived from subclonal populations of MDA-MBA-468 triple-negative breast cancer cells

2022-01-12 | GSE184541 | GEO

Transcriptome profiling of tumors from Kenyan triple negative breast cancer (TNBC) patients.

Project description:Triple negative breast cancer is an aggressive phenotypic breast cancer characterized by ER negative, PR negative and Her2 negative immunohistochemistry status. We embarked on a study to explore the transcriptome of Kenyan TNBC patients and identify potential biomarkers specific to Kenyan population. The transcriptome sequencing of tumors from Kenyan TNBC patients and comparisons with African American and Caucasian TNBC transcriptomes revealed several interesting targets and dysregulated pathways.

2021-04-28 | GSE142258 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

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