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Effect of Ptpn1/2 knockout on the transcriptome of unstimulated or IFN-beta stimulated B16-OVA cells

GSE297993 Mus musculus (mouse) RNA-seq (gene expression) 30 samples Submitted 2026/07/28 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 30 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
30 samples: 10 conditions, mostly in triplicateGroups 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)
Immune evasion by cancer cells remains a major barrier to the success of immune checkpoint blockade (ICB). Here, we identify the phosphatases PTPN1 and PTPN2 as cooperative regulators of tumor immune resistance. Dual genetic ablation or pharmacologic inhibition of PTPN1/2 enhances Type I and II interferon signaling, MHC-I and CXCL9 expression, and sensitizes tumor cells to cytotoxic T lymphocyte–mediated killing.
Read the full summary ↓
The small-molecule inhibitor KQ791 phenocopies these effects and synergizes with anti-PD1 therapy to suppress tumor growth in murine models, including immunotherapy-refractory cancers. Mechanistically, PTPN1/2 loss augments STAT1/3/5 signaling and primes cancer cells for immunogenic cell death via IFNγ/TNFα-induced pathways. Moreover, PTPN1/2 inhibition enhances antigen release and cross-presentation, promoting robust antigen-specific CD8⁺ T cell responses. These findings highlight PTPN1&2 as essential mediators of cancer immune evasion and support their inhibition as a strategy to broaden the effectiveness of immune checkpoint blockade in solid tumors.
This dataset
Open GSE297993 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 GSE297993_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 PRJNA1267080 and SRA study SRP587258. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 conditions, mostly in triplicate
CTL_USNT ×3 CTL_IFNb ×3 sgPtpn1_UNST ×3 sgPtpn1_IFNb ×3 sgPtpn2_UNST ×3 sgPtpn2_IFNb ×3 sgDKO_UNST ×3 sgDKO_IFNb ×3 +2 more

Supports a between-group comparison across 30 samples.

How we read this: 10 replicated groups read from 30 sample titles; they account for 30 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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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.