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IL-11 receptor is a novel target for drug development with pharmacological activity in fibro-inflammatory disease

GSE314304 Homo sapiens (human) RNA-seq (gene expression) 96 samples Submitted 2026/07/08 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 96 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
96 samples: 96 samples, each with a distinct title — no replicated groupsGroups 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
IL-11 receptor is a novel target for drug development with pharmacological activity in fibro-inflammatory diseaseScientific reports · 2026
Summary (written by the submitters)
IL-11, a novel target for drug development, has been associated with several fibroinflammatory diseases including thyroid eye disease (TED), where it plays an important role in signaling to stromal cells activating multiple intracellular pathways. In TED patient tissue, IL-11 is elevated and stimulates multiple effects important in disease progression, including the production of proinflammatory cytokines, hyaluronic acid (HA) and fibrotic markers.
Read the full summary ↓
LASN01, a potent antibody to IL-11 receptor, inhibits these effects and is a potential therapeutic agent for TED. Teprotumumab, an antibody to IGF-1 receptor, inhibits HA production and adipogenesis and is effective in reduction of proptosis. Activation of the IGF-1 and IL-11 pathways in TED tissue induces the expression of fibroinflammatory genes regulated by LASN01 and lipid biosynthetic genes regulated by Teprotumumab. Clinical studies show that LASN01 is well tolerated and in a placebo-controlled phase II trial in TED, LASN01 resulted in a statistically significant resolution of clinical activity score (CAS) in 88% of treated patients (p=0.028), but had lesser effects on proptosis. The data supports the importance of IL-11 biology in fibroinflammatory disease and that IL-11 receptor is a pharmacologically active target for drug development.
Published in
IL-11 receptor is a novel target for drug development with pharmacological activity in fibro-inflammatory disease
King DJ, Swaney JS, Rich C et al. · Scientific reports 2026 · PMID 42069852 · doi:10.1038/s41598-026-51600-0
This dataset
Open GSE314304 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 GSE314304_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 PRJNA1390692 and SRA study SRP656416. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42069852) ↗
Study design
96 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 96 sample titles: 96 distinct titles with little repetition. 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

+ 56 more — browse all 96 samples with per-sample file links →

Datasets on a similar topic

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.