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JNKinhibitors for the treatment of inflammation and endometriosis [epithelial cells]

GSE289058 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2026/07/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 10 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
10 samples: 5 conditions, mostly in duplicateGroups 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)
Endometriosis is a prevalent gynecological disease that impact ~10% of women of reproductive age. In addition to causing chronic pain, and inflammation, women with endometriosis experience high rates of infertility, migraine, inflammatory bowel disease and autoimmune conditions. In this study, the efficacy of newly developed inhibitors of the c-Jun N-terminal kinases (JNK) were tested as therapeutics for endometriosis.
Read the full summary ↓
Using state-of-the-art DNA encoded library screens, JNK inhibitors CDD-2728 and CDD-3013, with high specificity and efficacy were identified and tested in in vitro models of endometriosis. The ability of the inhibitors to decrease inflammation-related gene expression were evaluated in immortalized cell models of endometriosis, 12Z cells, and in primary derived endometriotic stromal cells from patients with the disease. Transcriptomic profiling was performed, as well as endpoints related to cell viability, cytotoxicity, and apoptosis. These studies identified that CDD-2728 and CDD-3013 were potent suppressors of IL1beta-induced inflammation, decreasing the expression of classical markers of inflammation, such as IL6, IL8, IL18, and PTGS2.
This dataset
Open GSE289058 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 GSE289058_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 PRJNA1220716. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
5 conditions, mostly in duplicate
12Z_Veh ×2 12Z_IL1B ×2 12Z_IL1+ 1µM CDD2728 ×2 12Z_IL1+ 10µM CDD2728 ×2 12Z_IL1+ 1µM CDD3013 ×2

Supports a between-group comparison across 10 samples.

How we read this: 5 replicated groups read from 10 sample titles; they account for 10 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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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.