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Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 response in mice and humans (RNA-Seq I).

GSE273487 Mus musculus (mouse) RNA-seq (gene expression) 23 samples Submitted 2025/05/04 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 23 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
23 samples: 11 conditions, mostly in duplicateGroups 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
Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 responseCell reports · 2025
Summary (written by the submitters)
Identifying host genetic factors modulating immune checkpoint inhibitor (ICI) efficacy has been experimentally challenging because of variations in both host and tumor genomes, differences in the microbiome, and patient life exposures. Utilizing the Collaborative Cross (CC) multi-parent mouse genetic resource population, we developed an approach that fixes the tumor genomic configuration while varying host genetics.
Read the full summary ↓
With this approach, we discovered that response to anti-PD-1 (aPD1) immunotherapy was significantly heritable in four distinct murine tumor models (H2 between 0.18-0.40). For the MC38 colorectal carcinoma system (H2 = 0.40), we mapped four significant ICI response quantitative trait loci (QTL) localized to mouse chromosomes (mChr) 5, 9, 15 and 17, and identified significant epistatic interactions between specific QTL pairs. Differentially expressed genes within these QTL were highly enriched for immune genes and pathways mediating allograft rejection and graft vs host disease. Using a cross species analytical approach, we found a core network of 48 genes within the four QTLs that showed significant prognostic value for overall survival in aPD1 treated human cohorts that outperformed all other existing validated immunotherapy biomarkers, especially in human tumors of the previously defined immune subtype 4. Functional blockade of two top candidate immune targets within the 48 gene network, GM-CSF and high affinity IL-2/IL-15 signaling, completely abrogated the MC38 tumor transcriptional response to aPD1 therapy in vivo. Thus, we have established a powerful cross species in vivo platform capable of uncovering host genetic factors that establish the tumor immune microenvironment configuration propitious for ICI response.
Published in
Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 response
Skelly DA, Graham JP, Cheng M et al. · Cell reports 2025 · PMID 40343794 · doi:10.1016/j.celrep.2025.115698
This dataset
Open GSE273487 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 GSE273487_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 PRJNA1142004 and SRA study SRP523183. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40343794) ↗
Study design
11 conditions, mostly in duplicate
MC38, C57BL/6J x CC001/UncJ host + isotype co… ×2 MC38, C57BL/6J x CC001/UncJ host + aPD1 biol ×2 MC38, C57BL/6J x CC002/UncJ host + isotype co… ×2 MC38, C57BL/6J x CC002/UncJ host + aPD1 biol ×2 MC38, C57BL/6J x CC075/UncJ host + isotype co… ×2 MC38, C57BL/6J x CC075/UncJ host + aPD1 biol ×2 MC38, C57BL/6J x CC036/UncJ host + isotype co… ×2 MC38, C57BL/6J x CC036/UncJ host + aPD1 biol ×2 +4 more

Supports a between-group comparison across 22 samples.

How we read this: 11 replicated groups read from 23 sample titles; they account for 22 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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