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Lineage Plasticity Driven by GATA6 Loss Fuels Colorectal Cancer Metastasis [H3K27ac_CUT&RUN]

GSE326232 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 8 samples Submitted 2026/06/22 Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 8 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
8 samples: 3 × Gata6KO_H3K27ac vs 3 × Control_H3K27acGroups 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)
Colorectal cancer (CRC) liver metastases are the leading cause of CRC-related mortality, yet the genetic and epigenetic drivers underlying this process remain poorly understood. Here, we established a pro-metastatic CRC organoid library through serial orthotopic transplantation of liver metastasis–derived organoids. Integrative RNA-seq and ATAC-seq analyses identified a pro-metastatic signature characterized by multilineage plasticity, including fetal-like and basal-like/squamous transcriptional programs.
Read the full summary ↓
Motif and transcription factor activity analyses identified GATA6 as a key regulator of these epigenetic alterations. GATA6 expression is downregulated in liver metastases, and its genetic ablation enhances liver metastasis with minimal effects on primary tumor growth. Mechanistically, GATA6 loss triggers pro-metastatic transcriptional programs, including fetal-like and basal-like/squamous states, accompanied by LGR5⁻ cell generation. This is mediated by direct repression of HNF4A and increased H3K27ac, and occurs independently of SOX17. Together, these findings identify GATA6 loss as a central regulator of multilineage plasticity that drives liver metastasis in CRC
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 GSE326232_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1444173 and SRA study SRP687269. Searching any of these in the dataset finder brings you back here.

Study design
3 × Gata6KO_H3K27ac vs 3 × Control_H3K27ac

Supports a between-group comparison across 6 samples.

How we read this: 2 replicated groups read from 8 sample titles; they account for 6 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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