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Assessing the impact of epigenetic inhibitors on reversion of the chromatin landscape from metastatic to non-metastatic organoids

GSE312105 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 18 samples Submitted 2026/01/08 Platform GPL30172
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 18 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
18 samples: 6 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)
Colorectal cancer, a leading cause of cancer-related mortality due to distant metastases, is driven by activating mutations in the Wnt and MAPK pathways. Understanding the interplay between these crucial pathways during metastatic progression is essential for developing effective treatments. Here we developed an immunocompetent mouse model of metastatic colorectal cancer using in vivo orthotopic passaging.
Read the full summary ↓
We demonstrate that highly metastatic tumor cells show increased accessibility of AP-1 TF motifs and less accessibility at TCF/LEF, suggesting higher MAPK and less WNT activity, respectively.
This dataset
Open GSE312105 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE312105_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1372181 and SRA study SRP650305. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in triplicate
p5 ×3 A485 ×3 EPZ004777 ×3 RG108 ×3 Panobinostat ×3 p1 ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.