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In vivo CRISPR screens in Head and Neck Cancer reveal that Uchl5 modulates extracellular matrix deposition to promote immune evasion [in vitro]

GSE269444 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/06/07 Platform GPL24247
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 × RNA-seq, MOC1-esc1 in vitro, sgCtrl, DMSO, vs 3 × RNA-seq, MOC1-esc1 in vitro, sgCtrl, IFNg, vs 3 × RNA-seq, MOC1-esc1 in vitro, sgUchl5, DMSO, vs 3 × RNA-seq, MOC1-esc1 in vitro, sgUchl5, IFNg,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)
Recurrent/metastatic head and neck squamous cell carcinoma (HNSCC) is an aggressive malignancy with a high unmet need for enhancing immunotherapy given current modest responses. Here, we performed an in vivo CRISPR screen in a HNSCC mouse model to identify immune evasion genes. We identified several epigenetic regulators of immune checkpoint blockade (ICB) response, including the ubiquitin C-terminal hydrolase 5 (UCHL5).
Read the full summary ↓
Loss of Uchl5 in tumors increased CD8+ T cell infiltration and improved ICB responses. Uchl5 deficiency reduced extracellular matrix (ECM) production and epithelial-mesenchymal-transition (EMT) transcriptional signatures, which contribute to stromal desmoplasia, a histologic finding associated with reduced anti-PD1 response in human HNSCCs. We identified a functional role for COL17A1, a collagen highly and specifically expressed in HNSCC, in Uchl5-mediated immune evasion. Our findings suggest an unappreciated role for UCHL5 in promoting EMT in HNSCC and highlight ECM modulation as a strategy to improve immunotherapy responses.
This dataset
Open GSE269444 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 GSE269444_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 PRJNA1121934 and SRA study SRP512792. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × RNA-seq, MOC1-esc1 in vitro, sgCtrl, DMSO, vs 3 × RNA-seq, MOC1-esc1 in vitro, sgCtrl, IFNg, vs 3 × RNA-seq, MOC1-esc1 in vitro, sgUchl5, DMSO, vs 3 × RNA-seq, MOC1-esc1 in vitro, sgUchl5, IFNg,

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
Datasets on a similar topic

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