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Single cell resolution of an open chromatin signature in persister tumor cells

GSE293459 Homo sapiens (human) Single-cell RNA-seq 30 samples Submitted 2025/11/13 Platform GPL20301
At a glance

Single-cell RNA-seq · human · 30 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Topic
Ovarian cancerThis series is part of our curated briefing on it.
Samples
30 samples: 9 × Multiome - GEX - PH vs 9 × Multiome - ATAC - PHGroups 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
Single-cell resolution of an open chromatin signature in persister tumor cellsCell reports · 2026
Summary (written by the submitters)
To characterize transcriptional and chromatin accessibility changes that promote survival of residual cancer following chemotherapy, we performed single-cell multiomic profiling (snRNA+snATAC) on a cohort of non-malignant fallopian tube, treatment-naive, and neoadjuvant chemotherapy (NACT)-treated high-grade serous ovarian cancer (HGSOC) samples. From this analysis, we identified an epigenetic signature that precedes expression and defines the drug-tolerant persister state.
Published in
Single-cell resolution of an open chromatin signature in persister tumor cells
Dumbrava MG, Mohammed Ismail W, Sandoval L et al. · Cell reports 2026 · PMID 41485222 · doi:10.1016/j.celrep.2025.116708
This dataset
Open GSE293459 in finder → Find more human RNA-seq datasets → Ovarian cancer 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 GSE293459_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1244735 and SRA study SRP575707. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41485222) ↗
Study design
9 × Multiome - GEX - PH vs 9 × Multiome - ATAC - PH

Supports a between-group comparison across 18 samples.

How we read this: 2 replicated groups read from 30 sample titles; they account for 18 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 Ovarian cancer 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.