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Loss of PTDSS1 in tumor cells improves immunogenicity and response to anti-PD-1 therapy [RNA-seq]

GSE292462 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/09/10 Platform GPL19057
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 × WT, vs 3 × Ptdss1 KD#1, vs 3 × Ptdss1 KD#2, vs 3 × Ptdss1 KD#3,Groups 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.
Summary (written by the submitters)
PTDSS1 (Phosphatidylserine synthase 1) encodes an enzyme that facilitates production of phosphatidylserine (PS), which mediates a global immunosuppressive signal. Here, based on in vivo CRISPR screen, we identified PTDSS1 as a target to improve anti-PD-1 therapy. Depletion of PTDSS1 in tumor cells increased expression of IFNγ-regulated genes, including B2m, Cxcl9, Cxcl10, and Stat1, even in the absence of IFNγ stimulation in vitro.
Read the full summary ↓
Loss of PTDSS1 in tumor cells also led to increased expression of MHC-I, which was associated with enhanced cytotoxicity of CD8+ T cells and increased frequency of an iNOS+ myeloid subset. A gene signature derived from the iNOS+ myeloid cell subset correlated with clinical benefit in patients treated with anti-PD-1 therapy. Moreover, genetic and pharmacological inhibition of PTDSS1 in different tumor models improved anti-PD-1 therapy. Together, our results provide insights on a new therapeutic strategy for overcoming immunosuppression by inhibiting PTDSS1 and provide rationale for development of a combination immunotherapy strategy comprised of PTDSS1 inhibition plus PD-1 blockade.
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 GSE292462_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 PRJNA1238825 and SRA study SRP571893. Searching any of these in the dataset finder brings you back here.

Study design
3 × WT, vs 3 × Ptdss1 KD#1, vs 3 × Ptdss1 KD#2, vs 3 × Ptdss1 KD#3,

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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