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Effect of SMARCA4 degradation on ID8 ovarian cancer cells senescent and not senescent.

GSE249062 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2024/09/19 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 24 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
Mus musculus (mouse)
Samples
24 samples: 6 × DMSO, vs 6 × AU15330 2.5uM, vs 6 × CISPLATIN 750nM, vs 6 × CISPLATIN 750nM+AU15330 2.5uM,Groups 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
SMARCA4 regulates the NK-mediated killing of senescent cellsScience advances · 2025
Summary (written by the submitters)
We report the analysis of RNA sequencing aimed at understanding the effects induced by AU-15330 (SMARCA4 PROTAC)-mediated degradation of SMARCA4 in P53-deficient senescent ID8 ovarian tumour cells. Specifically, we focus on exploring the repercussions of inhibiting SMARCA4, a constituent of the SWI/SNF complex subunit, on the SASP and immune activity within cisplatin-treated senescent cancer cells. The findings will help characterise the role of SMARCA4 inhibition on senescence surveillance by Natural Killer cells.
Published in
SMARCA4 regulates the NK-mediated killing of senescent cells
Reen V, D'Ambrosio M, Søgaard PP et al. · Science advances 2025 · PMID 39813356 · doi:10.1126/sciadv.adn2811
This dataset
Open GSE249062 in finder → Find more mouse 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 GSE249062_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 PRJNA1047102 and SRA study SRP475214. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39813356) ↗
Study design
6 × DMSO, vs 6 × AU15330 2.5uM, vs 6 × CISPLATIN 750nM, vs 6 × CISPLATIN 750nM+AU15330 2.5uM,

Supports a between-group comparison across 24 samples.

How we read this: 4 replicated groups read from 24 sample titles; they account for 24 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

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