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LAM cell mTOR dysregulation induces IL6 and paracrine AT2 cell senescence impeding lung repair in lymphangioleiomyomatosis.

GSE265851 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2025/08/05 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 30 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
30 samples: 30 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
mTOR dysregulation induces IL-6 and paracrine AT2 cell senescence impeding lung repair in lymphangioleiomyomatosisNature communications · 2025
Summary (written by the submitters)
LAM is a rare disease which causes lung cysts and respiratory failure. TSC2 deficient ‘LAM cells’ with dysregulated mTOR signalling form nodules with fibroblasts causing lung injury. We examined if mTOR dysregulation could induce senescence and impair responses to lung injury. Senescence markers p21 and p16 were increased in LAM lungs and co-localised with alveolar type 2 cells.
Read the full summary ↓
The SenMayo senescence gene panel was upregulated in LAM alveolar type 2 cells with senescence supressed by mTOR inhibition in patients. LAM cell / fibroblast spheroid cultures induced senescence markers in alveolar type 2 cell organoids, altered their growth and delayed epithelial scratch wound repair. Upstream regulator analysis predicted alveolar type 2 cell IL6 receptor activation. IL6 was produced by LAM cells, was overexpressed in LAM serum and related to lung function, induced p16 and p21 in alveolar type 2 cells and inhibited epithelial wound resolution. Wound repair in the presence of TSC2 null but not TSC2 addback LAM cell / fibroblast spheroids was enhanced by the IL6 receptor antagonist Tocilizumab. Our findings show TSC2 loss induces senescence and IL6 production which are associated with impaired lung repair. Targeting IL6 signalling in parallel with mTOR inhibition, may reduce lung damage in LAM.
Published in
mTOR dysregulation induces IL-6 and paracrine AT2 cell senescence impeding lung repair in lymphangioleiomyomatosis
Babaei-Jadidi R, Clements D, Wu Y et al. · Nature communications 2025 · PMID 41068078 · doi:10.1038/s41467-025-64036-3
This dataset
Open GSE265851 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 GSE265851_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 PRJNA1104541 and SRA study SRP504082. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41068078) ↗
Study design
30 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 30 sample titles: 30 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
Datasets on a similar topic

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