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Cxcr3 promotes protection from colorectal cancer liver metastasis by driving NK infiltration and plasticity

GSE266900 Mus musculus (mouse) Single-cell RNA-seq 18 samples Submitted 2025/03/14 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 18 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
18 samples: 6 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
Cxcr3 promotes protection from colorectal cancer liver metastasis by driving NK cell infiltration and plasticityThe Journal of clinical investigation · 2025
Summary (written by the submitters)
The anti-metastatic activity of NK cells is well established in several cancer types, but the mechanisms underlying NK cell metastasis infiltration and acquisition of anti-tumor characteristics remain unclear. Herein, we investigate the cellular and molecular factors required to facilitate the generation of an ILC1-like CD49a+NK cell population within the liver metastasis environment in orthotopic mouse models of colorectal cancer (CRC).
Read the full summary ↓
We show that CD49a+NK cells have the highest cytotoxic capacity among metastasis-infiltrating NK cells in the MC38 mouse model. Furthermore, the chemokine receptor CXCR3 promotes CD49a+NK cell accumulation and persistence in metastasis where NK cells co-localize with macrophages in CXCL9 and CXCL10 rich areas. We confirmed the accumulation of CXCR3+ NK cells in metastatic samples mined from a published sc-RNAseq dataset of a cohort of treatment-naïve CRC patients. Conditional deletion of Cxcr3 in NKp46+ cells and antibody-mediated depletion of metastasis-associated macrophages markedly impair CD49a+NK cell development, indicating that CXCR3 and macrophages contribute to efficient NK cell localization and polarization in liver metastasis. Conversely, CXCR3neg NK cells maintain a CD49a- phenotype in metastasis with reduced parenchymal infiltration and tumor killing capacity. Furthermore, CD49a+NK cell accumulation is impaired in an independent SL4-induced CRC metastasis model, which fails to accumulate CXCL9+ macrophages. Together, our results highlight a role for CXCR3/ligand axis in promoting macrophage-dependent NK cell accumulation and functional sustenance in liver metastasis from colorectal cancer.
Published in
Cxcr3 promotes protection from colorectal cancer liver metastasis by driving NK cell infiltration and plasticity
Russo E, D'Aquino C, Di Censo C et al. · The Journal of clinical investigation 2025 · PMID 40168086 · doi:10.1172/JCI184036
This dataset
Open GSE266900 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 GSE266900_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 PRJNA1108698 and SRA study SRP506178. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40168086) ↗
Study design
6 conditions, mostly in triplicate
Par_NK ×3 Tum_NK ×3 Par_ILC1 ×3 Tum_ILC1 ×3 MC38_H ×3 MC38_L ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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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