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Integrated computational analysis identifies therapeutic targets with dual action in cancer cells and T cells

GSE261915 Mus musculus (mouse) Single-cell RNA-seq 21 samples Submitted 2024/12/25 Platform GPL24676Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 21 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
21 samples: 7 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.
Paper
Integrated computational analysis identifies therapeutic targets with dual action in cancer cells and T cellsImmunity · 2025
Summary (written by the submitters)
Many cancer drugs that target cancer cell pathways have detrimental effects on the immune system. We developed a computational platform for the identification of therapeutic targets with beneficial effects in both cancer and immune cells. ICRAFT (https://icraft.pku-genomics.org/) enables integrated analysis of immune-related CRISPR screen datasets, scRNA-Seq data, and pre-treatment RNA-Seq data from clinical trials.
Read the full summary ↓
This platform enabled the discovery of a substantial number of targets with dual action in cancer cells and T cells. Among these, TNFAIP3, a ubiquitin-editing enzyme also known as A20, emerged as a leading target. Inactivating TNFAIP3 in cancer cells sensitizes them to immune attacks by activating the NF-κB pathway, while targeting it in T cells significantly enhances their antitumor efficacy.
Published in
Integrated computational analysis identifies therapeutic targets with dual action in cancer cells and T cells
Luo C, Zhang R, Guo R et al. · Immunity 2025 · PMID 40023158 · doi:10.1016/j.immuni.2025.02.007
This dataset
Open GSE261915 in finder → Find more 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 GSE261915_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1089567 and SRA study SRP496423. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40023158) ↗
Study design
7 conditions, mostly in triplicate
A549 cancer cell, sgTNFAIP3-1, ×3 A549 cancer cell, sgTNFAIP3-2, ×3 A549 cancer cell, sgCtrl, ×3 OT-1 cell, untreated, sgCtrl, ×3 OT-1 cell, sgCtrl, co-culture with cancer cel… ×3 OT-1 cell, sgTnfaip3-1, co-culture with cance… ×3 OT-1 cell, sgTnfaip3-2, co-culture with cance… ×3

Supports a between-group comparison across 21 samples.

How we read this: 7 replicated groups read from 21 sample titles; they account for 21 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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