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An endosomal toll-like receptor inhibitor drug with therapeutic effects in autoimmune diseases

GSE255890 Mus musculus (mouse) RNA-seq (gene expression) 10 samples Submitted 2024/02/29 Platform GPL21626
At a glance

RNA-seq (gene expression) · mouse · 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
Mus musculus (mouse)
Samples
10 samples
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
Discovery of ETI41 and ETI60: novel selective endosomal Toll-like receptor inhibitors for the treatment of autoimmune diseasesExperimental & molecular medicine · 2025
Summary (written by the submitters)
Autoimmune disease is a systemic inflammatory response of immune blood cells caused by self-tolerance dysfunction, due to genetic or environmental factors or a combination thereof. Studies on autoimmune disease regarding the inhibition of toll-like receptor (TLR)7/9-MyD axis or the regulation of plasmacytoid dendritic cells (pDCs) and Th17 comprising an abundance of respective receptors have shown improvements in phenotypes or molecular markers, providing clues to the practicality of the inhibitors of endosomal TLRs.
Read the full summary ↓
This study discovered several small-molecule compounds in endosomes exerting specific inhibitory effects on SITE1 shared among TLR 3, 7, 8, and 9, named endosomal TLR inhibitors (ETIs). The drug discovery process involved identifying lead compounds optimized to the receptors using a quantitative structure-activity relationship model and subsequent modification of the compounds to improve their binding affinity to target proteins. To propose a method of verifying the drug effects against side or placebo effect arising from false positives, the drug evaluation process converged from cellular response to signaling process to protein binding. Drug values on the inhibition of endosomal TLRs in autoimmune disease were assessed based on the onset of mild-to-life-threatening autoimmune disease including psoriasis, systemic lupus erythematosus, and multiple sclerosis. Complete healing was achieved for psoriasis through direct or indirect association with TLRs. Therapeutic potential of the novel ETIs for psoriasis was verified and is considered an effective drug for other autoimmune diseases associated with the TLR7/9-MyD axis.
Published in
Discovery of ETI41 and ETI60: novel selective endosomal Toll-like receptor inhibitors for the treatment of autoimmune diseases
Jeong U, Lee WH, Choi YS et al. · Experimental & molecular medicine 2025 · PMID 40887497 · doi:10.1038/s12276-025-01526-w
This dataset
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.

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 GSE255890_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1076919 and SRA study SRP503411. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 10 more — browse all 10 samples with per-sample file links →

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