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Genome-wide identification of DOT1L-regulated targets via H3K79me2 modification in SW1990 pancreatic cancer cells

GSE303754 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 2 samples Submitted 2026/07/28 Platform GPL34284
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 2 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
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
2 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)
Disruption of epigenetic regulation plays a pivotal role in pancreatic cancer progression, yet the genome-wide targets of DOT1L-mediated histone H3 lysine 79 dimethylation (H3K79me2) remain poorly defined. In this study, we investigated the epigenetic landscape regulated by DOT1L in SW1990 pancreatic ductal adenocarcinoma cells. Cells were treated with EPZ-5676, a selective DOT1L inhibitor, or vehicle control, followed by chromatin immunoprecipitation sequencing (ChIP-seq) using an H3K79me2-specific antibody.
Read the full summary ↓
We identified differentially enriched regions between EPZ-5676-treated and untreated cells, reflecting global loss of H3K79me2 upon DOT1L inhibition. Integration with gene annotation data revealed putative DOT1L-regulated genes involved in transcriptional regulation, cell proliferation, and cancer signaling pathways. These findings provide insight into the role of DOT1L in maintaining the active chromatin state and transcriptional programs in pancreatic cancer cells and highlight potential therapeutic targets in epigenetic intervention.
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 GSE303754_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 PRJNA1297609 and SRA study SRP603911. Searching any of these in the dataset finder brings you back here.

Samples in this study

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