GEO series

The endothelin-1-driven tumor-stroma feed-forward loops in high-grade serous ovarian cancer

GSE268498 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/07/17 Platform GPL18573

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 × Untreated HG-SOC cells vs 3 × ET-1 stimulated HG-SOC cells vs 3 × MAC treated HG-SOC cells vs 3 × MAC+ET-1 treated HG-SOC cellsGroups 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: The endothelin-1-driven tumor-stroma feed-forward loops in high-grade serous ovarian cancerClinical science (London, England : 1979) · 2024

Summary (written by the submitters)

The high-grade serous ovarian cancer (HG-SOC) tumor microenvironment (TME) is constellated by cellular elements and a network of soluble constituents that contribute to tumor progression. In the multitude of the secreted molecules, the endothelin-1 (ET-1) has emerged to be implicated in the tumor/TME interplay, however the molecular mechanisms induced by the ET-1-driven feed-forward loops (FFL) and associated with the HG-SOC metastatic potential need to be further investigated.

Read the full summary ↓

The tracking of the patient-derived (PD) HG-SOC cell transcriptome by RNA-seq identified the vascular endothelial growth factor (VEGF) gene and its associated signature among those mostly upregulated by ET-1 and down-modulated by the dual ET-1R antagonist macitentan. Within the ligand-receptor pairs concurrently expressed in PD-HG-SOC cells, endothelial cells and activated fibroblasts, we discovered two intertwined FFL, the ET-1/ET-1R and VEGF/VEGF receptors, concurrently activated by ET-1 and shutting-down by macitentan, or by the anti-VEGF antibody bevacizumab. In parallel, we observed that ET-1 fine-tuned the tumoral and stromal secretome towards a pro-invasive pattern. Into the fray of the HG-SOC/TME double and triple co-cultures, the secretion of ET-1 and VEGF, that share a common co-regulation, was inhibited upon the administration of macitentan. Functionally, macitentan, mimicking the effect of bevacizumab, interfered with the HG-SOC/TME FFL-driven communication that fuel the HG-SOC invasive behaviour. The identification of ET-1 and VEGF FFL as tumor and TME actionable vulnerabilities, reveal how ET-1R blockade, targeting the HG-SOC cells and the TME simultaneously, may represent an effective therapeutic option for HG-SOC patients.

Published in

The endothelin-1-driven tumor-stroma feed-forward loops in high-grade serous ovarian cancer

Tocci P, Roman C, Sestito R et al. · Clinical science (London, England : 1979) 2024 · PMID 38884602 · doi:10.1042/CS20240346

This dataset

Open GSE268498 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 GSE268498_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 PRJNA1117462 and SRA study SRP510313. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38884602) ↗

Study design

3 × Untreated HG-SOC cells vs 3 × ET-1 stimulated HG-SOC cells vs 3 × MAC treated HG-SOC cells vs 3 × MAC+ET-1 treated HG-SOC cells

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

GSM8292041 Untreated HG-SOC cells rep1 Untreated HG-SOC cells
GSM8292042 Untreated HG-SOC cells rep2 Untreated HG-SOC cells
GSM8292043 Untreated HG-SOC cells rep3 Untreated HG-SOC cells
GSM8292044 ET-1 stimulated HG-SOC cells rep1 ET-1 stimulated HG-SOC …
GSM8292045 ET-1 stimulated HG-SOC cells rep2 ET-1 stimulated HG-SOC …
GSM8292046 ET-1 stimulated HG-SOC cells rep3 ET-1 stimulated HG-SOC …
GSM8292047 MAC treated HG-SOC cells rep1 MAC treated HG-SOC cells
GSM8292048 MAC treated HG-SOC cells rep2 MAC treated HG-SOC cells
GSM8292049 MAC treated HG-SOC cells rep3 MAC treated HG-SOC cells
GSM8292050 MAC+ET-1 treated HG-SOC cells rep1 MAC+ET-1 treated HG-SOC…
GSM8292051 MAC+ET-1 treated HG-SOC cells rep2 MAC+ET-1 treated HG-SOC…
GSM8292052 MAC+ET-1 treated HG-SOC cells rep3 MAC+ET-1 treated HG-SOC…

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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.