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Extrachromosomal DNA Associates with Nuclear Condensates and Reorganizes Chromatin Structures to Enhance Oncogenic Transcription [RNA-seq II]

GSE275705 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2025/09/18 Platform GPL34284Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 36 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
36 samples: 12 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.
Paper
Extrachromosomal DNA associates with nuclear condensates and reorganizes chromatin structures to enhance oncogenic transcriptionCancer cell · 2025
Summary (written by the submitters)
Extrachromosomal, circular DNA (ecDNA) is a prevalent and significant oncogenic alteration in cancer genomes. Its frequency is associated with aggressive tumor behavior and poor patient outcome. To understand how ecDNA promotes oncogenesis, we map ecDNA-associated chromatin complexes at single-molecule resolution in three well-characterized ecDNA+ cancer models that harbor different oncogenes.
Read the full summary ↓
Using a suite of 3D genome mapping and imaging analyses, we determined ecDNA nuclear organization and uncovered that ecDNA hubs are part of MED1-mediated condensates that can be rapidly disrupted by agents perturbing liquid-liquid phase separation (LLPS). The functional relevance of ecDNA condensates was demonstrated by inhibition of LLPS which led to hub dispersal, the reduction of MED1 co-activator binding, inhibition of oncogenic transcription and selectively increase cell death of ecDNA-containing cells across a broad range of cancer models. Robust epigenetically silencing of the regulatory modules within ecDNAs effectively disrupts ecDNA’s mode of actions and demonstrates the causality between ecDNA enhancer function, chromosomal contacts, transcription and cellular proliferation, which directly corroborate ecDNA’s trans-activator activity. Our findings reveal that ecDNA drives tumor promotion activity through nuclear condensate and suggests that exploiting these nuclear structures may serve as a universal strategy against malignant tumors. Our work elucidates the structures, functions and regulation of ecDNA which is expected to transform the paradigm for studying cancer genomes and expand the current views of how oncogenes are regulated, from which new clinical strategies can be realized.
Published in
Extrachromosomal DNA associates with nuclear condensates and reorganizes chromatin structures to enhance oncogenic transcription
Taghbalout A, Tung CH, Clow PA et al. · Cancer cell 2025 · PMID 40972571 · doi:10.1016/j.ccell.2025.08.008
This dataset
Open GSE275705 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 GSE275705_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 PRJNA1152594 and SRA study SRP528741. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40972571) ↗
Study design
12 conditions, mostly in triplicate
PC3DM_RNA-seq-vector ×3 PC3DM_RNA-seq-ecSE1-perturbation ×3 PC3DM_RNA-seq-ecSE2-perturbation ×3 PC3DM_RNA-seq-ecSE6-perturbation ×3 PC3DM_RNA-seq-ecSE7-perturbation ×3 PC3DM_RNA-seq-ecSEcombo-perturbation ×3 COLO320DM_RNA-seq-vector ×3 COLO320DM_RNA-seq-ecSE1-perturbation ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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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