Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Single cell RNA-seq of brain glioblastoma samples

ABSTRACT: Single cell RNA-seq of brain glioblastoma samples

PROVIDER: PRJNA682432 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR13194337_1.fastq.gz	Fastqsanger.gz
	SRR13194337_2.fastq.gz	Fastqsanger.gz
	SRR13194338_1.fastq.gz	Fastqsanger.gz
	SRR13194338_2.fastq.gz	Fastqsanger.gz
	SRR13194339_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 16

Similar Datasets

Single cell RNA-seq of brain glioblastoma samples

Project description:Glioblastomas (GBM) are the most aggressive type of brain tumors with a dismal prognosis. The effectiveness of anti-tumor drugs is thwarted by brain endothelial cells (ECs) in the tumor microenvironment. However, the characteristics of ECs remains poorly inventoried at the single-cell level. We performed single-cell RNA sequencing (scRNA-seq) for ECs from 4 GBMs and matching non-malignant brain samples, and identified distinct EC phenotypes in GBM.

2021-07-08 | GSE162631 | GEO

Single-cell RNA-seq of traumatic brain injury samples

Project description:Single-cell RNA-seq of traumatic brain injury samples

| PRJNA756100 | ENA

scRNA-Seq analysis of adult glioblastoma patient samples

Project description:Glioblastoma is the most common type of malignant brain tumor among adults. We used single-cell RNA sequencing (scRNA-seq) to analyze the diversity of glioblastoma cells.

2024-07-25 | GSE214966 | GEO

Expression data from glioblastoma tissue and normal brain tissue samples (from epilepsy surgery)

Project description:The characterization of glioblastoma has provided invaluable data related to this molecularly heterogeneous disease. Recent advances in high-throughput microarrays have received extensive attention and made substantial progress in reconstructing the gene regulatory network of medical biology. Using microarray analysis, significant differences in gene expression between normal and disease tissues have been observed. However, as a result of the underlying shortcomings of microarray technology, such as small sample size, measurement error, and information insufficiency, unveiling this disease mechanism has remained a major challenge to glioblastoma research. Hence, GO, pathway information, network-based approaches and machine learning algorithms have been employed to identify the mechanisms underlying this disease. We identified the differentially expressed genes (DEGs) between 9 glioblastoma samples and 9 normal brain samples.

2017-02-10 | GSE90886 | GEO

Single-cell RNA-seq characterization of glioblastoma

Project description:Single-cell RNA-seq characterization of glioblastoma

| PRJNA929553 | ENA

Single-cell RNA sequencing analysis of mouse normal brain and GBM tumors

Project description:To investigate the transcriotome in glioblastoma tumor and normal brain on a single cell level, we performed RNA sequcening analysis with single cells derived from mouse normal brain tissue or GBM tumor tissue. Particularly, vascular endothelial cells (ECs) were traced using a Cdh5-Cre;LSL-tdTomato system.

2023-02-17 | GSE199379 | GEO

Single Cell RNA-seq of Glioblastoma Tumors and GBOs

Project description:Analysis of glioblastoma tissue and corresponding glioblastoma organoids by single cell RNA sequencing.

2019-12-26 | GSE141946 | GEO

Single cell RNA sequencing of three IDHwt glioblastoma patient tumors

Project description:Single cell RNA sequencing was performed to allow expression-based identification of tumor versus normal cells from glioblastoma patient specimens. Identified tumor cells were then analyzed to assess the expression tumor-cell specific expression of TRIM26, WWP2, and SOX2.

2021-09-25 | E-MTAB-9435 | biostudies-arrayexpress

Single Cell Spatial Analysis Reveals the Topology of Immunomodulatory Purinergic Signaling in Glioblastoma

Project description:Abstract from manuscript Glioblastoma develops an immunosuppressive microenvironment that fosters tumorigenesis and resistance to current therapeutic strategies. Here we use multiplexed tissue imaging and single-cell RNA-sequencing to characterize the composition, spatial organization, and clinical significance of extracellular purinergic signaling in glioblastoma. We show that glioblastoma exhibit strong expression of CD39 and CD73 ectoenzymes, correlating with increased adenosine levels. Microglia are the predominant source of CD39, while CD73 is principally expressed by tumor cells, particularly in tumors with amplification of EGFR and astrocyte-like differentiation. Spatially-resolved single-cell analyses demonstrate strong spatial correlation between tumor CD73 and microglial CD39, and that their spatial proximity is associated with poor clinical outcomes. Together, this data reveals that tumor CD73 expression correlates with tumor genotype, lineage differentiation, and functional states, and that core purine regulatory enzymes expressed by neoplastic and tumor-associated myeloid cells interact to promote a distinctive adenosine-rich signaling niche and immunosuppressive microenvironment potentially amenable to therapeutic targeting.

2022-06-27 | ST002203 | MetabolomicsWorkbench

Single cell transcriptome profiling of the human alcohol-dependent brain samples.

Project description:Single cell transcriptome profiling of the human alcohol-dependent brain samples.

| PRJNA593861 | ENA