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Effect of AU-15330 treatment on Z138 gene expression profile

GSE303024 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/07/16 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × Z138_8h_AU-15330 vs 3 × Z138_24h_AU-15330 vs 3 × Z138_8h_DMSO vs 3 × Z138_24h_DMSOGroups 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
The SOX11:SMARCA4 complex is a driver of oncogenic transcriptional programs in mantle cell lymphomaBlood cancer journal · 2025
Summary (written by the submitters)
AU-15330 treatment RNA-seq dataset: Fastq transcriptomic sequencing files from Z138 mantle cell lymphoma (MCL) cell line treated with the SMARCA4 degrader AU-15530. Cells were treated for 8 or 24 hours with 0.5 μM AU-15530 or control (DMSO). The dataset includes 3 biological replicates per condition (AU-15530 8h, AU-15530 24h, DMSO 8h, DMSO 24h).
Published in
The SOX11:SMARCA4 complex is a driver of oncogenic transcriptional programs in mantle cell lymphoma
De Bolòs A, Carreras-Caballé M, Sureda-Gómez M et al. · Blood cancer journal 2025 · PMID 40739087 · doi:10.1038/s41408-025-01333-6
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 GSE303024_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: 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 PRJNA1293361 and SRA study SRP601802. Searching any of these in the dataset finder brings you back here.

Study design
3 × Z138_8h_AU-15330 vs 3 × Z138_24h_AU-15330 vs 3 × Z138_8h_DMSO vs 3 × Z138_24h_DMSO

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
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