GEO series

BRD9 Reads Lactate-Induced H3K18 Lactylation to Drive Oncogenic Chromatin Remodeling in Hepatocellular Carcinoma

GSE314155 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 17 samples Submitted 2026/03/05 Platform GPL29480

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.
Paper: BRD9 recognizes lactate-induced H3K18 lactylation to drive oncogenic chromatin remodeling in hepatocellular carcinomaCell death and differentiation · 2026

Summary (written by the submitters)

Histone lactylation bridges glycolytic metabolism to oncogenic transcription, but its mechanistic readers remain poorly defined. Here, we identify bromodomain-containing protein 9 (BRD9) as a lactyl-lysine reader that links lactate-driven H3K18 lactylation (H3K18la) to chromatin remodeling in hepatocellular carcinoma (HCC). Clinically, elevated H3K18la levels correlate with poor HCC prognosis.

Read the full summary ↓

Structural (NMR) and biophysical analyses demonstrate BRD9’s bromodomain engages H3K18la through its acetyl-lysine pocket with weak, transient affinity, distinct from stable H3K18ac binding, enabling lactate-dependent chromatin interactions. Multi-omics profiling reveals H3K18la recruits BRD9 and the non-canonical BRG1-associated factor (ncBAF) complex to active enhancers and promoters, promoting chromatin accessibility and oncogenic transcription (SPARC, TMEM64, ANGEL1, SCARB1). Glycolytic inhibition or BRD9 targeting displaces BRD9 from chromatin, suppresses oncogenes, and impairs HCC proliferation. p300 or HDAC inhibition attenuates H3K18la-driven oncogenic transcription and tumor viability. Our findings establish BRD9 as a metabolic-epigenetic mediator that translates glycolytic flux into chromatin remodeling, offering actionable therapeutic targets for HCC.

Published in

BRD9 recognizes lactate-induced H3K18 lactylation to drive oncogenic chromatin remodeling in hepatocellular carcinoma

Wei E, Ji D, Jia Y et al. · Cell death and differentiation 2026 · PMID 41792243 · doi:10.1038/s41418-026-01698-6

This dataset

Open GSE314155 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 GSE314155_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 PRJNA1390174 and SRA study SRP656365. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41792243) ↗

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

GSM9382806 NC_1, HepG2 cells, untreated, 24 h
GSM9382807 NC_2, HepG2 cells, untreated, 24 h
GSM9382808 NC_3, HepG2 cells, untreated, 24 h
GSM9382809 2-DG_1, HepG2 cells, 2-DG treated, 48 h
GSM9382810 2-DG_2, HepG2 cells, 2-DG treated, 48 h
GSM9382811 2-DG_3, HepG2 cells, 2-DG treated, 48 h
GSM9382812 Nala_1, HepG2 cells, Nala treated, 48 h
GSM9382813 Nala_2, HepG2 cells, Nala treated, 48 h
GSM9382814 Nala_3, HepG2 cells, Nala treated, 48 h
GSM9382815 NC_Input, Hepg2 cells, untreated, 48 h
GSM9382816 NC_H3K18la, Hepg2 cells, untreated, 48 h
GSM9382817 NC_BRD9, Hepg2 cells, untreated, 48 h
GSM9382818 2-DG_Input, HepG2 cells, 2-DG treated, 48 h
GSM9382819 2-DG_H3K18la, HepG2 cells, 2-DG treated, 48 h
GSM9382820 2-DG_BRD9, HepG2 cells, 2-DG treated, 48 h
GSM9382821 NC, Hepg2 cells, untreated, 48 h
GSM9382822 2-DG, Hepg2 cells, 2-DG treated, 48 h

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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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