GEO series

RNA-seq and ATAC-seq analysis of 5-azacytidine-treated HepG2 cells reveals epigenetic reactivation of BFL-1 and SQOR in hepatocellular carcinoma

GSE300717 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 17 samples Submitted 2026/08/01 Platform GPL24676Platform GPL20795

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 17 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: Hepatocellular carcinomaThis series is part of our curated briefing on it.
Samples: 17 samples: 17 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)

Hepatocellular carcinoma (HCC) remains a major therapeutic challenge with poor prognosis due to treatment resistance. Epigenetic silencing of tumor suppressor genes through promoter hypermethylation contributes to oncogenesis and resistance to cell death stimuli. We employed low-concentration 5-azacytidine (5-AZA) treatment to identify epigenetically silenced genes that modulate cell death susceptibility in HepG2 hepatocellular carcinoma cells without inducing baseline cytotoxicity.

Read the full summary ↓

HepG2 cells were treated with 0, 2, and 10 μM 5-azacytidine for 4 days, followed by integrative RNA-seq and ATAC-seq analysis to characterize transcriptomic changes and chromatin accessibility patterns. This approach revealed coordinated promoter opening and transcriptional reactivation of methylation-silenced genes, particularly BFL-1 (BCL2A1) and SQOR, whose reactivation enhanced cell death susceptibility to TNF-α/CHX and sorafenib treatments. Our findings provide mechanistic insights into epigenetic vulnerabilities in HCC and demonstrate the utility of multi-omics approaches for identifying therapeutically tractable targets for precision epigenetic editing strategies.

This dataset

Open GSE300717 in finder → Find more human RNA-seq datasets → Hepatocellular carcinoma landscape →

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 GSE300717_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 PRJNA1281900 and SRA study SRP594486. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

17 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 17 sample titles: 17 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

GSM9067164 HepG2, 0uM 5-azacytidine, rep1, ATAC-seq
GSM9067165 HepG2, 0uM 5-azacytidine, rep2, ATAC-seq
GSM9067166 HepG2, 0uM 5-azacytidine, rep3, ATAC-seq
GSM9067167 HepG2, 2uM 5-azacytidine, rep1, ATAC-seq
GSM9067168 HepG2, 2uM 5-azacytidine, rep2, ATAC-seq
GSM9067169 HepG2, 2uM 5-azacytidine, rep3, ATAC-seq
GSM9067170 HepG2, 10uM 5-azacytidine, rep1, ATAC-seq
GSM9067171 HepG2, 10uM 5-azacytidine, rep2, ATAC-seq
GSM9067172 HepG2, 0uM 5-azacytidine, rep1, RNA-seq
GSM9067173 HepG2, 0uM 5-azacytidine, rep2, RNA-seq
GSM9067174 HepG2, 0uM 5-azacytidine, rep3, RNA-seq
GSM9067175 HepG2, 2uM 5-azacytidine, rep1, RNA-seq
GSM9067176 HepG2, 2uM 5-azacytidine, rep2, RNA-seq
GSM9067177 HepG2, 2uM 5-azacytidine, rep3, RNA-seq
GSM9067178 HepG2, 10uM 5-azacytidine, rep1, RNA-seq
GSM9067179 HepG2, 10uM 5-azacytidine, rep2, RNA-seq
GSM9067180 HepG2, 10uM 5-azacytidine, rep3, RNA-seq

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GSE107170 Molecular Signature of Hepatitis D Virus-Associated Hepatocellular Carcinoma 307 samples same disease briefing · shares hepatocellular
GSE109211 Molecular predictors of prevention of recurrence in hepatocellular carcinoma with sorafenib as adjuvant treatment in the phase 3 STORM trial 140 samples same disease briefing · shares hepatocellular
GSE10186 Integrative Transcriptome Analysis Reveals Common Molecular Subtypes of Human Hepatocellular Carcinoma 118 samples same disease briefing · shares hepatocellular
GSE105130 Comprehensive analysis of Transcriptome Profiles in Hepatocellular Carcinoma patients 52 samples same disease briefing · shares hepatocellular
GSE140228 Landscape and Dynamics of Single Immune Cells in Hepatocellular Carcinoma 41 samples same disease briefing · shares hepatocellular
GSE114564 Identification of novel serum biomarkers in early-stage HCC patients. 118 samples same disease briefing

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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.