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Context-dependent effect of glucocorticoid receptor activity shapes ovarian cancer cell plasticity and therapy response

GSE309650 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/03/04 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × SKVO3 cells, shEmpty - 2D vs 3 × SKVO3 cells, shNR3C1y - 2D vs 3 × SKVO3 cells, shEmpty - 3D vs 3 × SKVO3 cells, shNR3C1y - 3DGroups 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
Context-dependent effect of glucocorticoid receptor activity shapes ovarian cancer cell plasticity and therapy responseMolecular cancer · 2026
Summary (written by the submitters)
The phenotypic plasticity of cancer cells, i.e. their adaptability to a variable/ stressful environment, is fundamental for disease progression/aggressiveness. Here we revealed that the glucocorticoid receptor (GR, NR3C1), a key player in the human response to stress, controls proliferation, morphology, motility/invasion, and the gene expression profile of high-grade serous ovarian carcinoma (hereafter OC) cells.
Read the full summary ↓
By modulating glucose metabolism, GR acts as a tumor suppressor delaying ovarian cancer growth under 3D-settings. Conversely, under 2D conditions GR acts as a tumor promoter, driving cell mesenchymalization, increasing cell motility and chemoresistance. Strikingly, modulators of glucose metabolism as metformin and 2-deoxyglucose, are alone sufficient to induce similar cell behavioural changes. So, in ovarian cancer a GR-glucose metabolism axis modulates a escaping signalling response triggered by stressful (3D overgrowth, starvation) condition.
Published in
Context-dependent effect of glucocorticoid receptor activity shapes ovarian cancer cell plasticity and therapy response
De Girolamo M, Ibello E, Improda T et al. · Molecular cancer 2026 · PMID 41821050 · doi:10.1186/s12943-026-02630-9
This dataset
Open GSE309650 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 GSE309650_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 PRJNA1336678 and SRA study SRP630034. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41821050) ↗
Study design
3 × SKVO3 cells, shEmpty - 2D vs 3 × SKVO3 cells, shNR3C1y - 2D vs 3 × SKVO3 cells, shEmpty - 3D vs 3 × SKVO3 cells, shNR3C1y - 3D

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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.