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A Natural Cyclic Peptide Enhances Cytotoxic Th9 Differentiation and Antitumor Immunity

GSE295054 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/11/28 Platform GPL34290
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: 3 × DMSO vs 3 × EpA vs 3 × DMSO fato vs 3 × EpA fatoGroups 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
A fungi-derived cyclic peptide enhances Th9-mediated antitumor immunity by targeting ZAP70 and SREBP1The Journal of clinical investigation · 2026
Summary (written by the submitters)
Adoptive cell therapy (ACT) relies on durable and functional T cells to mediate tumor clearance. Th9 cells are a metabolically fit CD4⁺ T cell subset with strong persistence but limited cytotoxicity. Here, we identify Endomelipaneptide A (EpA), a cyclic peptide from Ganoderma lucidum–associated endophytic fungi, as a potent enhancer of Th9 differentiation. EpA promotes a cytotoxic Th9 phenotype with enhanced mitochondrial function and metabolic fitness.
Published in
A fungi-derived cyclic peptide enhances Th9-mediated antitumor immunity by targeting ZAP70 and SREBP1
Zhao W, Zhou Y, Chen Y et al. · The Journal of clinical investigation 2026 · PMID 41364522 · doi:10.1172/JCI196907
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 GSE295054_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 PRJNA1252720 and SRA study SRP579691. Searching any of these in the dataset finder brings you back here.

Study design
3 × DMSO vs 3 × EpA vs 3 × DMSO fato vs 3 × EpA fato

Supports a between-group comparison across 12 samples.

How we read this: 4 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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