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Lysosomal exocytosis by macrophages as a druggable mechanism for anti-inflammatory clearance of dead adipocytes in adipose tissue

GSE307090 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2025/09/03 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 4 × Apilimod treated and isolated ATMs_sample vs 4 × DMSO treated and isolated ATMs_sample vs 4 × Lalistat treated and isolated ATMs_sample vs 4 × Rapamycin treated and isolated ATMs_sampleGroups 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
Lysosomal exocytosis by macrophages as a druggable mechanism for anti-inflammatory clearance of dead adipocytes in adipose tissueCell death & disease · 2025
Summary (written by the submitters)
The clearance of dead adipocytes in adipose tissue (AT) poses a major challenge due to their large size, which exceeds the phagocytic capacity of macrophages and prevents classical, anti-inflammatory efferocytosis. Instead, adipose tissue macrophages (ATMs) accumulate around dying adipocytes, forming crown-like structures (CLS), and engage in lysosomal exocytosis – the extracellular degradation of adipocytes.
Read the full summary ↓
In this study, we used an ex vivo explant model of murine epididymal white AT, cultured over seven days to investigate pharmacological strategies that modulate lysosomal exocytosis. We observed a progressive increase in CLS formation, secretion of the lysosomal enzymes ß-Hexosaminidase A (HEXA) and lysosomal acid lipase (LAL), and surface abundance of LAMP1 and LAMP2, confirming ATMs as key mediators of this process. Notably, activation of lysosomal exocytosis with the mTOR inhibitor Rapamycin enhanced adipocyte clearance and significantly reduced inflammatory ATM abundance and TNF-α secretion. Bulk RNA sequencing of ATMs revealed a highly significant impact of Rapamyin on ATM proliferation. In contrast, inhibition of lysosomal exocytosis with PIKfyve inhibitor Apilimod or targeted inhibition of LAL using Lalistat-2 disrupted lysosomal function and promoted a pro-inflammatory ATM phenotype. Our findings highlight lysosomal exocytosis as a critical pathway for the resolution of dead adipocytes and the regulation of inflammation in adipose tissue. Pharmacological enhancement of this process may represent a promising therapeutic approach to attenuate inflammation in AT and its metabolic consequences, including insulin resistance and type 2 diabetes.
Published in
Lysosomal exocytosis by macrophages as a druggable mechanism for anti-inflammatory clearance of dead adipocytes in adipose tissue
Wehr R, Lindhorst A, Arndt L et al. · Cell death & disease 2025 · PMID 41436477 · doi:10.1038/s41419-025-08334-0
This dataset
Open GSE307090 in finder → Find more mouse 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 GSE307090_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 PRJNA1314244 and SRA study SRP616615. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41436477) ↗
Study design
4 × Apilimod treated and isolated ATMs_sample vs 4 × DMSO treated and isolated ATMs_sample vs 4 × Lalistat treated and isolated ATMs_sample vs 4 × Rapamycin treated and isolated ATMs_sample

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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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