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Glioblastoma cells imitate neuronal excitability in humans

GSE315516 Homo sapiens (human) Single-cell RNA-seq 82 samples Submitted 2026/04/01 Platform GPL18573
At a glance

Single-cell RNA-seq · human · 82 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Topic
GlioblastomaThis series is part of our curated briefing on it.
Samples
82 samples: 44 × aAP vs 38 × noGroups 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
Combined patch-clamp electrophysiology and single-cell genomic analysis reveal spiking tumor cells at the neocortical glioblastoma interface in humansNeuro-oncology · 2026
Summary (written by the submitters)
Background: Glioblastomas are renowned for their pronounced intratumoral heterogeneity, characterized by a diverse array of plastic cell types. However, the physiological and transcriptomic features of the cells residing in the invasive leading edge (LE), including both neurons and glioblastoma cells (GBCs), remain unclear, challenging our comprehension of the glioblastoma pathophysiology.
Read the full summary ↓
Methods: To elucidate molecular and morphophysiological features of LE cells, we established an experimental workflow enabling the investigation of GBCs and neurons within cancer-infiltrated organotypic tissue specimens from the same patients. With this approach, we characterized the electrophysiological properties of cells in the neocortical tumor LE (LE cells). We further performed single-cell Patch-seq experiments, enabling transcriptomic analysis of electrophysiologically recorded LE cells. Results: Upon depolarization, 58% of LE cells exhibited aberrant action potentials (aAPs). Electrophysiological assessment showed that a subset of GBCs generated aAPs, with no significant differences in aAP propertiescompared to LE neurons. Transcriptomic analysis of 144 LE cells revealed four transcriptomic clusters, including two GBC populations and two neuronal populations. LE GBCs exhibited diverse cellular states, including mesenchymal-like, astrocyte-like, neural progenitor-like, and oligodendrocyte-precursor cell-like phenotypes. Notably, LE GBCs exhibiting aAPs displayed reduced mitotic pathway activity and developmental regulatory ionchannel CaV1.2. Cell-cell interaction analysis illustrates a higher signaling interaction between aAP LE cells compared to no-aAP LE cells. Conclusion: In summary, we find comparable electrical properties between neurons and a subset of GBCs in the leading edge, suggesting an active electrophysiological role of GBCs in the tumor's pathophysiology.
Published in
Combined patch-clamp electrophysiology and single-cell genomic analysis reveal spiking tumor cells at the neocortical glioblastoma interface in humans
Tong T, Hendriksen JD, Elbæk KJ et al. · Neuro-oncology 2026 · PMID 41857760 · doi:10.1093/neuonc/noag059
This dataset
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.

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 GSE315516_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1398184. Searching any of these in the dataset finder brings you back here.

Study design
44 × aAP vs 38 × no

Supports a between-group comparison across 82 samples.

How we read this: 2 replicated groups read from 82 sample titles; they account for 82 of them. 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

+ 42 more — browse all 82 samples with per-sample file links →

More Glioblastoma datasets

Search all human RNA-seq datasets in GEO →

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