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Integrative epigenomic profiling of hepatocellular carcinoma uncovers aberrant cis-regulatory changes and potential prognostic indicators [RNA-seq]

GSE276133 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2025/02/28 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 10 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Hepatocellular carcinomaThis series is part of our curated briefing on it.
Samples
10 samples: 2 × RNAseq_HepG2_sgLuci vs 2 × RNAseq_HepG2_THE1D_sg vs 2 × RNAseq_PLC_sgLuci vs 2 × RNAseq_PLC_HERVE_int_sg244Groups 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
Multi-omic analysis of hepatocellular carcinoma reveals aberrant cis-regulatory changes and dysregulated retrotransposons with prognostic potentialCommunications biology · 2025
Summary (written by the submitters)
Hepatocellular carcinoma (HCC) exhibits widespread epigenetic aberrations; however, the underlying transcriptional regulatory landscape remains underexplored. Here, we performed integrated analyses with genome-wide profiles of the transcriptomes, histone modifications and DNA methylation from patient-derived HCC tumors and controls.
Read the full summary ↓
We identified both global and focal epigenetic alterations including large-scale DNA methylation loss, and dysregulation of cis-regulatory elements (CREs) associated with genes involved in cell cycle control, immune responses, and extracellular matrix organization. Notably, we discovered that transcriptional upregulation of Glypican-3 (GPC3), a diagnostic biomarker and immunotherapeutic target for HCC, was linked to the reactivation of a fetal liver super-enhancer (SE). This SE, in concert with DNA hypomethylation of two CpG islands, modulated GPC3 expression. Global DNA hypomethylation also contributed to transcriptional dysregulation of retrotransposon-derived CREs. Specifically, we observed that patients with high expression of a HERVE-int-driven long non-coding RNA transcript showed poorer disease outcomes and specific molecular signatures associated with better response to immunotherapy. Our results highlight this and other retrotransposons as potential prognostic indicators and a predictive signature for immunotherapy response. Taken together, our findings provide insights into the role of epigenetic dysregulation of CREs and retrotransposons in hepatocarcinogenesis, which could benefit the clinical management of HCC.
Published in
Multi-omic analysis of hepatocellular carcinoma reveals aberrant cis-regulatory changes and dysregulated retrotransposons with prognostic potential
Cheng CCY, Cheung MF, Lee AY et al. · Communications biology 2025 · PMID 41390797 · doi:10.1038/s42003-025-09154-w
This dataset
Open GSE276133 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 GSE276133_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1154965 and SRA study SRP529843. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41390797) ↗
Study design
2 × RNAseq_HepG2_sgLuci vs 2 × RNAseq_HepG2_THE1D_sg vs 2 × RNAseq_PLC_sgLuci vs 2 × RNAseq_PLC_HERVE_int_sg244

Supports a between-group comparison across 8 samples.

How we read this: 4 replicated groups read from 10 sample titles; they account for 8 of them. 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 Hepatocellular carcinoma datasets

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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.