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Epigenetic reprogramming of the mesenchymal state by SUV39H1/H2 [ChIP-Seq]

GSE206726 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 42 samples Submitted 2025/06/20 Platform GPL24676Platform GPL18573
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 42 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)
Samples
42 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.
Summary (written by the submitters)
Emergence of chemotherapy resistance is a major clinical challenge resulting in large number of deaths yearly. One mechanism involves epigenetic reprogramming through which cancer cells acquire mesenchymal (M) properties akin to cancer stem cells. How cells epigenetically establish resistance to chemotherapy is largely unknown. Here, we show that the two human lysine 9 histone H3 (H3K9) methyltransferase proteins (SUV39H1 and SUV39H2) play a central role in maintaining mesenchymal, chemotherapy resistant state in several cancer models.
Read the full summary ↓
More importantly, a transient inhibition of these enzymes results in an epigenetic change, triggering a mesenchymal-to-epithelial transition and sensitizing these cells to chemotherapy. These data expand the functional repertoire of SUV39H family of proteins in eukaryotes and expose new therapeutic targets for neutralizing chemotherapy resistance in cancers.
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 GSE206726_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 PRJNA851827. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 42 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

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