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RNA sequencing of WT and TrIP KO P14 TCR Tg T cells stimulated in vitro

GSE302184 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/07/10 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 18 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
18 samples
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)
The protein PI3K-interacting protein (PIK3IP1), or transmembrane inhibitor of PI3K (TrIP), is highly expressed by T cells and can modulate PI3K activity in these cells. Several studies have also revealed that TrIP is rapidly downregulated following T cell activation and can play important roles in T cell differentiation. We have generated mice with CD8-specific TrIP deficiency.
Read the full summary ↓
Here we provide data detailing that activated TrIP KO CD8 T cells display an increased inflammatory transcriptional profile in the absence of TrIP. Consistent with these effects, we also show that knockout of TrIP specifically in CD8 T cells resulted in reduced growth of syngeneic tumors. When characterizing the tumor-infiltrating cells, we found that TrIP KO led to an increase in the number of tumor-infiltrating T cells, as well as a delay in the acquisition of an exhausted phenotype, based on phenotypic and transcriptomic analyses. Finally, our data suggest that TrIP regulates the diversity of T cell clonal responses to tumors, since we observed an increase in the number of distinct T cell clonotypes responding to a tumor neoantigen. Taken together, we show that TrIP intrinsically restricts the CD8 T cell response to tumors, and that targeting TrIP may augment the anti-tumor response in a way that is distinct from established checkpoint therapies.
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 GSE302184_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 PRJNA1289150 and SRA study SRP599666. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 18 more — browse all 18 samples with per-sample file links →

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