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Microbiota-indole-3-propionic acid-heart axis mediates the protection of leflunomide against αPD1-induced cardiotoxicity in mice

GSE286252 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/02/01 Platform GPL28330
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 4 × aPD1_lef vs 4 × aPD1_veh vs 4 × IgG_lefGroups 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
Microbiota-indole-3-propionic acid-heart axis mediates the protection of leflunomide against αPD1-induced cardiotoxicity in miceNature communications · 2025
Summary (written by the submitters)
Anti-programmed death 1 (αPD1) immune checkpoint blockade is used in combination for cancer treatment but associated with cardiovascular toxicity. Finding drugs that suppress cardiovascular toxicity but not compromise the efficacy of αPD1-mediated immunotherapy is of great importance. Leflunomide (Lef) can suppress the growth of several tumor and mitigate cardiac remodeling in mice. However, the specific role of Lef in αPD1-induced cardiotoxicity remains unclear.
Published in
Microbiota-indole-3-propionic acid-heart axis mediates the protection of leflunomide against αPD1-induced cardiotoxicity in mice
Huang R, Shen ZY, Huang D et al. · Nature communications 2025 · PMID 40108157 · doi:10.1038/s41467-025-58107-8
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 GSE286252_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 PRJNA1208476 and SRA study SRP556285. Searching any of these in the dataset finder brings you back here.

Study design
4 × aPD1_lef vs 4 × aPD1_veh vs 4 × IgG_lef

Supports a between-group comparison across 12 samples.

How we read this: 3 replicated groups read from 12 sample titles; they account for 12 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
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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.