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The tumor suppressor SMAD4 is a gatekeeper for genome stability

GSE292334 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2026/07/14 Platform GPL20301
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.
Summary (written by the submitters)
Cancer chromosomal instability (CIN) causes structural and numerical chromosome aberrations and acts as a driver for tumor progression and poor patient outcome. However, the mechanisms driving CIN are incompletely understood. In this study, we identified SMAD4, a key tumor suppressor in colorectal and pancreatic cancers, as a gatekeeper for genome stability.
Read the full summary ↓
Loss of SMAD4 results in homologous recombination DNA repair defects, DNA replication stress and mitotic errors, resulting in genome instability. SMAD4 acts as part of BMP signaling and ensures genome stability through its transcriptional target inhibitor of DNA binding 3 (ID3). Consequently, abrogation of BMP signaling or ID3 phenocopies the genome maintenance defects induced upon loss of SMAD4. Thus, our study defines SMAD4 as a key suppressor of genome instability in human cancer.
This dataset
Open GSE292334 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 GSE292334_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 PRJNA1238182 and SRA study SRP571509. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 conditions, mostly in triplicate
HCT116-WT_ biol ×3 HCT116-WT_ BMPRi_biol ×3 HCT116-SMAD4-/-_ biol ×3 HT29_vector-control_biol ×3 HT29_SMAD4_biol ×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

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