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Hypoxia-induced phase separation of ZHX2 drives 3D chromatin remodeling and cancer metastasis (RNA-Seq)

GSE260794 Homo sapiens (human) RNA-seq (gene expression) 45 samples Submitted 2025/03/18 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 45 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
45 samples: 15 conditions, mostly in triplicateGroups 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)
Hypoxia and dysregulation of three-dimensional (3D) chromatin architecture can both activate oncogenic transcriptomic profiles, thus contributing to tumor malignancy. But how hypoxia regulates 3D chromatin architecture remains unknown.
Read the full summary ↓
Here, we find that the transcription factor, zinc fingers and homeoboxes 2 (ZHX2), generates liquid-liquid phase separation (LLPS) under hypoxia, thus promoting its occupancy on chromatin and activating transcription for a cluster of oncogenes, that is enriched by metastatic genes distinct from targets of hypoxia-inducible factor (HIF) and pathologically relevant to breast cancer. Mechanistically, hypoxia induces the LLPS of ZHX2 via a proline-rich intrinsically disordered region (IDR) in the nuclear localization sequence (NLS), thereby enhancing the phosphorylation of ZHX2 at S625 and S628 that incorporates CCCTCbinding factor (CTCF) in condensates to reorganize chromatin looping, consequently resulting in oncogenic super-enhancer formation and breast cancer metastasis. This fundamental mechanism provides significant insight into oncogene activation and suggests a phase separation-based therapeutic strategy for cancer.
This dataset
Open GSE260794 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 GSE260794_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 PRJNA1083513 and SRA study SRP493193. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
15 conditions, mostly in triplicate
T47D, shCtrl, Normoxia, RNA, ×3 T47D, shCtrl, Hypoxia, RNA, ×3 T47D, shZHX2, Hypoxia, RNA, ×3 T47D, Ctrl, Hypoxia, RNA, ×3 T47D, 0.5%1,6HD, Hypoxia, RNA, ×3 T47D, 1%1,6HD, Hypoxia, RNA, ×3 T47D, shCtrl, vector, hypoxia, ×3 T47D, shZHX2, vector, hypoxia, ×3 +7 more

Supports a between-group comparison across 45 samples.

How we read this: 15 replicated groups read from 45 sample titles; they account for 45 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

+ 5 more — browse all 45 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.