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Transcriptional effects of co-culture on the spatiotemporal dynamics of T cell motility and cancer-T cell interactions [bulk_seq_invivo]

GSE293495 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2025/04/08 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 12 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
12 samples: 3 × B16-F10 vs 3 × B16-OVAGroups 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
Deciphering antigen-specific T cell navigation tactics and cancer immune evasion in co-culturesCommunications biology · 2025
Summary (written by the submitters)
Insufficient infiltration of cytotoxic T cells into solid tumors poses a major challenge in cancer immunotherapy, largely due to the intricate tumor microenvironment. To address this, we co-cultured mouse cancer cell lines (B16-WT or B16-OVA) with cancer-specific cytotoxic T cells (activated OT-1) in vitro to uncover the impact of cancer-T cell interactions on T cell motility, pivotal for effective tumor infiltration.
Read the full summary ↓
To investigate the potential molecular mechanisms underlying T cell motility patterns in the two coculture contexts, we performed both bulk and single-cell RNA sequencing of cancer and T cells sorted from the co-culture systems at specific time points.
Published in
Deciphering antigen-specific T cell navigation tactics and cancer immune evasion in co-cultures
Li X, Jin T, Wang L et al. · Communications biology 2025 · PMID 40745217 · doi:10.1038/s42003-025-08568-w
This dataset
Open GSE293495 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 GSE293495_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 PRJNA1244808 and SRA study SRP575796. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40745217) ↗
Study design
3 × B16-F10 vs 3 × B16-OVA

Supports a between-group comparison across 6 samples.

How we read this: 2 replicated groups read from 12 sample titles; they account for 6 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

Search all mouse RNA-seq datasets in GEO →

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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.