← BioTransfer GEO Dataset Finder
GEO series

Reprogramming of Cellular Plasticity via ETS and MYC Core-regulatory circuits During Response to MAPK Inhibition in BRAF-mutant colorectal cancer

GSE280280 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 36 samples Submitted 2026/04/24 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 36 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
Homo sapiens (human)
Topic
Colorectal cancerThis series is part of our curated briefing on it.
Samples
36 samples: 36 samples, each with a distinct title — no replicated groupsGroups 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)
Background: Aberrant enhancer dynamics play a critical role in the initiation and progression of colorectal cancer (CRC). BRAFV600E-mutated metastatic CRC may be a unique subtype, exhibiting a strong epigenetic phenotype. Interestingly, bromodomain 2, a reader protein for H3K27ac-marked enhancers, was found to be synthetically lethal in CRC with BRAF + EGFR inhibition.
Read the full summary ↓
Design: We evaluated the effectiveness of targeting aberrant enhancers with bromodomain and extraterminal (BET) + MAPK pathway inhibitors in patient-derived xenograft models of metastatic CRC, followed by comprehensive profiling of transcriptomic and chromatin dynamics upon BET inhibitor combination treatment. Results: The combination of BET and standard MAPK inhibitors has demonstrated improved efficacy against BRAFV600E CRC and selective improvements against RAS-mutant CRC in vivo. We showed that BET + MAPK inhibition induced a profound downregulation of the MAPK signaling pathway compared to MAPK inhibition alone. The loss of activation signal on enhancers, as determined by H3K27ac, led to dysregulation of core-regulatory circuitries of CRC, especially loss of the auto-regulatory mechanism of the MAPK downstream E26 transformation–specific transcription factor family. Single nucleus multiome (RNA + ATAC) sequencing further distinguished differential transcriptomic and chromatin dynamics at cell type levels. Profound downregulation of well-differentiated cell types confirmed deep inhibition of MAPK signaling and downstream transcription factors. On the other hand, dedifferentiated cell populations were abundant after MAPK or combination inhibition, suggesting therapy-induced cell state switching and adaptation. Conclusion: We are evaluating BET + BRAF + EGFR inhibition in patients with treatment-refractory BRAFV600E metastatic CRC. ClinicalTrial.gov identifier: NCT06102902.
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 GSE280280_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 PRJNA1177515 and SRA study SRP540717. Searching any of these in the dataset finder brings you back here.

Study design
36 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 36 sample titles: 36 distinct titles with little repetition. 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
More Colorectal cancer datasets

Search all human ChIP / ATAC / CUT&Tag datasets in GEO →

Share this dataset

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.