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Coordinated gene expression within persistent STAT3-associated chromatin conformations contributes to hepatocellular carcinoma progression [RNA-seq]

GSE275342 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2025/11/26 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 16 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)
Samples
16 samples: 4 × Hep3BnIL6_RNA-seq vs 4 × Hep3BpIL6_RNA-seq vs 4 × Huh7nIL6_RNA-seq vs 4 × Huh7pIL6_RNA-seqGroups 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
Coordinated gene expression within sustained STAT3-associated chromatin conformations contributes to hepatocellular carcinoma progressionCancer communications (London, England) · 2025
Summary (written by the submitters)
p-STAT3 has emerged as a critical modulator of hepatocellular carcinoma (HCC) progression; however, its role in 3D chromatin architecture and the expression of genes linked to HCC aggressiveness remains largely unexplored. Here, we elucidate the function of p-STAT3 in establishing stable regulatory regions known as FIREs, characterized by highly active interactions and the potential to alter topologically associated domains (TADs).
Read the full summary ↓
Our results demonstrate that expression of genes located within FIREs is highly correlated, and upregulation, these genes play a crucial role in driving phenotypes, including HCC invasion and tube formation. Notably, p-STAT3-associated FIREs maintain chromatin activation despite pharmacological interventions targeting STAT3, suggesting a mechanism that failure to suppress the expression of genes associated with HCC aggressiveness leads to drug resistance. These findings provide novel insights into how the 3D genome structure associated with p-STAT3 promotes HCC progression and drug resistance, highlighting the therapeutic potential of targeting 3D chromatin dynamics in HCC.
Published in
Coordinated gene expression within sustained STAT3-associated chromatin conformations contributes to hepatocellular carcinoma progression
Jang S, Yoon S, Yang H et al. · Cancer communications (London, England) 2025 · PMID 40715029 · doi:10.1002/cac2.70049
This dataset
Open GSE275342 in finder → Find more human RNA-seq datasets →
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 GSE275342_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 PRJNA1150499 and SRA study SRP527733. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40715029) ↗
Study design
4 × Hep3BnIL6_RNA-seq vs 4 × Hep3BpIL6_RNA-seq vs 4 × Huh7nIL6_RNA-seq vs 4 × Huh7pIL6_RNA-seq

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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
Datasets on a similar topic

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