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SMARCA4 Inhibits Breast Tumor progression through Transcriptional Activation of GTPase Activating Factor ARHGAP29 and RHOA Suppression [RNA]

GSE261368 Homo sapiens (human) RNA-seq (gene expression) 11 samples Submitted 2025/02/12 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 11 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
Breast cancerThis series is part of our curated briefing on it.
Samples
11 samples
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 Inhibits Breast Cancer Progression and Metastasis through RHOA SuppressionCancer research · 2025
Summary (written by the submitters)
The chromatin-remodeling SWI/SNF complex emerged as a potent suppressor of tumor spheroid growth. SMARCA4 was identified as a top candidate to suppress TNBC growth in 3D tumor spheroid model using genome-wide CRISPR screen. Specifically, the loss of the SWI/SNF ATPase subunit SMARCA4 promotes tumor spheroid growth with reduced compactness, and enhanced the growth in breast primary tumors and metastasis across multiple breast cancer models.
Read the full summary ↓
Further investigations revealed its function in inhibiting the RHOA pathway. SMARCA4 is required for the transcription of Rho GTPase activating factor ARHGAP29, achieved through direct binding to its promoter to provide DNA accessibility. The loss of SMARCA4 resulted in reduced ARHGAP29 levels and hyperactive RHOA signaling. This subsequently disrupted cell adhesion, facilitated a loose spheroid structure and promoted spheroid growth.
Published in
SMARCA4 Inhibits Breast Cancer Progression and Metastasis through RHOA Suppression
Sun Z, Li Z, Wei Y et al. · Cancer research 2025 · PMID 39992701 · doi:10.1158/0008-5472.CAN-24-2801
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 GSE261368_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 PRJNA1086790 and SRA study SRP494692. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 11 more — browse all 11 samples with per-sample file links →

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