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Depletion of PCCB and/or PIK3CA from pancreatic tumor cells KPC influences T cells infiltrating to TME

GSE254041 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2024/03/01 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: 12 samples, each with a distinct title — no replicated groupsGroups 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
Propionyl-CoA carboxylase subunit B regulates anti-tumor T cells in a pancreatic cancer mouse modeleLife · 2025
Summary (written by the submitters)
Most human pancreatic ductal adenocarcinoma (PDAC) are not infiltrated with cytotoxic T cells and are highly resistant to immunotherapy. Our previous study demonstrated that ablation of Pik3ca in KPC (KrasG12D; Trp53R172H; Pdx1-Cre) pancreatic cancer cells induced host T cells to infiltrate and completely eliminate the tumors in a syngeneic orthotopic implantation mouse model.
Read the full summary ↓
Here we report that implantation of Pik3ca-/- KPC (named αKO) cancer cells induces clonal expansion of cytotoxic T cells infiltrating the pancreatic tumors in this mouse model. To identify potential molecules that can regulate the activity of these anti-tumor T cells, we conducted an in vivo genome-wide gene-deletion screen using αKO cells implanted in the mouse pancreas and the result shows that deletion of propionyl-CoA carboxylase subunit B gene (Pccb) in αKO cells (named p-αKO) leads to immune evasion, tumor progression and death of host mice. Surprisingly, p-αKO tumors are still infiltrated with T cells but they are inactive against tumor cells. However, blockade of PD-L1/PD1 interaction reactivated clonally expanded T cells infiltrating p-αKO tumors, leading slower tumor progression and improve survival of host mice. These results indicate that Pccb can modulate the activity of cytotoxic T cells infiltrating some pancreatic tumors and this understanding may help to improve immunotherapy for PDAC.
Published in
Propionyl-CoA carboxylase subunit B regulates anti-tumor T cells in a pancreatic cancer mouse model
Han HV, Efem R, Rosati B et al. · eLife 2025 · PMID 40067762 · doi:10.7554/eLife.96925
This dataset
Open GSE254041 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 GSE254041_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 PRJNA1067366 and SRA study SRP485063. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40067762) ↗
Study design
12 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 12 sample titles: 12 distinct titles with little repetition. 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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