← BioTransfer GEO Dataset Finder
GEO series

Multi-omics Dissection of MAPK-driven Senescence Unveils Therapeutic Vulnerabilities in KIAA1549::BRAF-fusion Pediatric Low-Grade Glioma Models

GSE287599 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2025/06/24 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 15 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)
Samples
15 samples: 5 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.
Paper
Multi-omics dissection of MAPK-driven senescence unveils therapeutic vulnerabilities in KIAA1549::BRAF-fusion pediatric low-grade glioma modelsSignal transduction and targeted therapy · 2025
Summary (written by the submitters)
Pilocytic astrocytomas (PA), the most common pediatric low-grade gliomas (pLGGs), are characterized by genetic MAPK pathway alterations leading to constitutive activation and oncogene-induced senescence (OIS) accompanied with the senescence-associated secretory phenotype (SASP). This study investigates the molecular mechanisms of signaling pathways regulating OIS and SASP in pLGGs using a multi-omics approach.
Read the full summary ↓
We utilized senescent DKFZ-BT66 cells derived from a primary KIAA1549::BRAF-fusion positive PA to generate RNA-sequencing and phospho-/proteomic datasets before and after treatment with the MEK inhibitor trametinib. Multi-omics factor analysis (MEFISTO) and single sample gene set enrichment analysis (ssGSEA) were employed to identify key OIS effectors and differentially regulated pathways upon MAPK inhibition. Trametinib treatment inhibited MAPK activity, OIS and SASP signatures across all omics levels, functionally underscored by reduced sensitivity towards senolytic drugs. We constructed a pathway network using a prior knowledge approach, mapping n = 106 upregulated and n = 84 downregulated direct downstream effectors of MAPK leading to OIS/SASP. These effectors are associated with better progression-free survival in pLGG patients, independent of tumor site, level of resection, and genetic aberration. Several compounds targeting signaling nodes (SOD-1, IRS1, CDK1/2, CK2) involved in OIS and under MAPK control were identified, of which n = 4 were validated in an additional primary KIAA1549::BRAF fusion pLGG model as potential new therapeutic vulnerabilities for the treatment of pLGG. Our unbiased multi-omics signaling pathway analysis identifies a specific and comprehensive network of MAPK-OIS-SASP interdependencies in pLGGs and suggests new therapeutic strategies for these tumors.
Published in
Multi-omics dissection of MAPK-driven senescence unveils therapeutic vulnerabilities in KIAA1549::BRAF-fusion pediatric low-grade glioma models
Sigaud R, Stefanski A, Selt F et al. · Signal transduction and targeted therapy 2025 · PMID 40550805 · doi:10.1038/s41392-025-02279-8
This dataset
Open GSE287599 in finder → Find more human 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 GSE287599_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 PRJNA1213793 and SRA study SRP558748. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40550805) ↗
Study design
5 conditions, mostly in triplicate
DKFZ-BT66-OFF_Ctrl ×3 DKFZ-BT66-OFF_100nM trametinib 15min ×3 DKFZ-BT66-OFF_100nM trametinib 1h ×3 DKFZ-BT66-OFF_100nM trametinib 6h ×3 DKFZ-BT66-OFF_100nM trametinib 24h ×3

Supports a between-group comparison across 15 samples.

How we read this: 5 replicated groups read from 15 sample titles; they account for 15 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
Datasets on a similar topic

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.