← BioTransfer GEO Dataset Finder
GEO series

GSK3 acts as a switch for transcriptional programs in a model of low-grade gliomagenesis

GSE295254 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/04/25 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Lower-grade gliomaThis series is part of our curated briefing on it.
Samples
18 samples: 6 conditions, mostly in triplicateGroups 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.
Summary (written by the submitters)
Mutations in isocitrate dehydrogenase (IDH)-1/2 are defining drivers of low-grade gliomagenesis. However, mutant IDH alone is not sufficient for malignant transformation, and additional events are required for the development of low-grade glioma. While specific genetic lesions have been identified to contribute to low-grade gliomagenesis, less is known about the signaling pathways involved in acquiring malignancy.
Read the full summary ↓
To identify prerequisites of IDH mutant tumorigenesis, we modulated pathways previously implicated in glioma initiation using a tractable in vitro model system for early IDH1R132H-dependent gliomagenesis. Through the use of chemical compounds, we targeted WNT/GSK3, TGF-β and NOTCH-signaling, assessing their functional, transcriptional, and translational impacts. Expression of LGG-related marker L1CAM was affected by perturbation of all pathways, though only modulation of WNT/GSK3-signaling resulted in profound molecular transformation, including glioma-associated genes and programs regulating cellular architecture and cell replication. This was accompanied by altered cell morphology, migration capacity, and enhanced proliferation. Transcription factor RUNX2 was identified as a potential downstream effector, whose inhibition abrogated cell proliferation. Disrupted WNT/GSK3 signaling in a model system of early low-grade gliomagenesis fundamentally impacted cell fate, as demonstrated by a reshaped transcriptional landscape, aberrant transcription factor activity, ECM restructuring, and altered proliferation capacity. Our data suggests that GSK3 may play a central role during low-grade gliomagenesis, warranting further investigation.
This dataset
Open GSE295254 in finder → Find more human RNA-seq datasets → Lower-grade glioma 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 GSE295254_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1253969 and SRA study SRP580389. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
IDH1R132H immortalized human astrocytes, cont… ×3 IDH1R132H immortalized human astrocytes, CHIR… ×3 IDH1R132H immortalized human astrocytes, Reps… ×3 IDH1R132H immortalized human astrocytes, YO-0… ×3 IDH1R132H immortalized human astrocytes, sico… ×3 IDH1R132H immortalized human astrocytes, siRU… ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
More Lower-grade glioma datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.