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Recognition of ubiquitinated histone H2A constitutes a treatment target for RSF1-driven ovarian cancer [RNA-seq]

GSE281128 Homo sapiens (human) RNA-seq (gene expression) 13 samples Submitted 2025/03/01 Platform GPL24676Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 13 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
Ovarian cancerThis series is part of our curated briefing on it.
Samples
13 samples: 5 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)
RNA-seq results revealed that overexpression of RSF1, but not RSF1ΔUAB, induced a gene expression program enriched for cancer stem cell markers. Conversely, overexpression of a UAB domain decoy peptide reduced cell proliferation and blocked the cancer stem cell gene expression programs in OVCAR3 cells. Together, these studies reveal the critical role of recognizing H2Aub in RSF1-driven ovarian cancer and demonstrate that the interaction between RSF1 and H2Aub constitutes a druggable target for treating ovarian cancers with high levels of RSF1.
This dataset
Open GSE281128 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 GSE281128_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 PRJNA1182350 and SRA study SRP543322. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 conditions, mostly in triplicate
SKOV3, control, ×3 SKOV3, RSF1 overexpression, ×3 SKOV3, RSF1delUAB overexpression, ×3 OVCAR3, control, ×2 OVCAR3, UAB, ×2

Supports a case/control comparison: 6 samples read as cases, 5 as controls.

How we read this: 5 replicated groups read from 13 sample titles; they account for 13 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

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.