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Mesenchymal glioma stem cells trigger vasectasia, a distinct neovascularization process mediated by extracellular vesicles carrying EGFR [scRNA-seq]

GSE207360 Mus musculus (mouse) Single-cell RNA-seq 45 samples Submitted 2024/03/04 Platform GPL24247Platform GPL25431Platform GPL26526
At a glance

Single-cell RNA-seq · mouse · 45 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
45 samples: 45 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Mesenchymal glioma stem cells trigger vasectasia-distinct neovascularization process stimulated by extracellular vesicles carrying EGFRNature communications · 2024
Summary (written by the submitters)
To investigate the functional role of EGFR in the formation of large vessels, we established a mesenchymal glioma stem cell line (GSC83) with intact EGFR and knocked down EGFR by Crispr-Cas9. We then performed single cells gene expression profiling analysis using data obtained from RNA-seq of 2 different tumours, derived by injection of GSC83 WT or GSC83 KO in NSG mice. In addition, GSC83 WT or GSC83 KO tumours in NSG mice were subjected to spatial gene expression profiling in situ using GeoMX platform.
Published in
Mesenchymal glioma stem cells trigger vasectasia-distinct neovascularization process stimulated by extracellular vesicles carrying EGFR
Spinelli C, Adnani L, Meehan B et al. · Nature communications 2024 · PMID 38570528 · doi:10.1038/s41467-024-46597-x
This dataset
Open GSE207360 in finder → Find more RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE207360_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA854923 and SRA study SRP384582. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38570528) ↗
Study design
45 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 45 sample titles: 45 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 5 more — browse all 45 samples with per-sample file links →

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Share this dataset

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