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Glioblastoma scRNA-seq shows treatment-induced, immune-dependent increase in mesenchymal cancer cells and structural variants in distal neural stem cells

GSE278450 Homo sapiens (human) Single-cell RNA-seq 22 samples Submitted 2024/10/25 Platform GPL20301
At a glance

Single-cell RNA-seq · human · 22 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Topic
GlioblastomaThis series is part of our curated briefing on it.
Samples
22 samples: 22 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
Glioblastoma scRNA-seq shows treatment-induced, immune-dependent increase in mesenchymal cancer cells and structural variants in distal neural stem cellsNeuro-oncology · 2022
Summary (written by the submitters)
Glioblastoma is a treatment-resistant brain cancer. Its hierarchical cellular nature and its tumor microenvironment (TME) before, during, and after treatments remain unresolved. Here, we used single-cell RNA sequencing to analyze new and recurrent glioblastoma and the nearby subventricular zone (SVZ). We found 4 glioblastoma neural lineages are present in new and recurrent glioblastoma with an enrichment of the cancer mesenchymal lineage, immune cells, and reactive astrocytes in early recurrences.
Read the full summary ↓
Cancer lineages were hierarchically organized around cycling oligodendrocytic and astrocytic progenitors that are transcriptomically similar but distinct to SVZ neural stem cells (NSCs). Furthermore, NSCs from the SVZ of patients with glioblastoma harbored glioblastoma chromosomal anomalies. Lastly, mesenchymal cancer cells and TME reactive astrocytes shared similar gene signatures which were induced by radiotherapy in a myeloid-dependent fashion in vivo. These data reveal the dynamic, immune-dependent nature of glioblastoma’s response to treatments and identify distant NSCs as likely cells of origin.
Published in
Glioblastoma scRNA-seq shows treatment-induced, immune-dependent increase in mesenchymal cancer cells and structural variants in distal neural stem cells
Couturier CP, Nadaf J, Li Z et al. · Neuro-oncology 2022 · PMID 35416251 · doi:10.1093/neuonc/noac085
This dataset
Open GSE278450 in finder → Find more human RNA-seq datasets → Glioblastoma landscape →
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 GSE278450_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 PRJNA1167282. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 35416251) ↗
Study design
22 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 22 sample titles: 22 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
More Glioblastoma datasets

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.