GEO series

A dual TGF-β-driven immunosuppressive mechanism controls T cell recruitment and expansion in metastatic colorectal cancer

GSE272376 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/07/25 Platform GPL30172

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: TGF-β builds a dual immune barrier in colorectal cancer by impairing T cell recruitment and instructing immunosuppressive SPP1(+) macrophagesNature genetics · 2025

Summary (written by the submitters)

Poor prognosis colorectal cancer (CRC) is characterized by an immune suppressive TGF-β-activated tumor microenvironment (TME). Pharmacological inhibition of TGF-β signaling promotes T cell infiltration and synergizes with immune checkpoint blockade (ICB) to eliminate metastatic disease in experimental models. Through genetic dissection in model systems and analysis of patient datasets, here we uncover a network of genetic programs regulated by TGF-β signaling in liver metastasis.

Read the full summary ↓

We show that productive immune responses require both continuous recruitment of tumor-specific CD8+ T cells and subsequent clonal expansion in the TME. TGF-β signaling prevents the recruitment of memory CD8+ T cells by enforcing residence in the lymph nodes. In the absence of newly arrived T cells, the response of tumor-resident T cells to immunotherapy is insufficient to eradicate metastases. We further unveil a genetic program induced by TGF-β in macrophages, which characterizes CRC patients with a high risk of developing metastatic disease. TGF-β-activated macrophages prevent the clonal expansion of newly arrived T cells in the TME through the extracellular matrix protein osteopontin. Overall, our findings reveal how TGF-β signaling integrates immune-suppressive responses in the innate and adaptive immune systems to enable metastatic outgrowth.

Published in

TGF-β builds a dual immune barrier in colorectal cancer by impairing T cell recruitment and instructing immunosuppressive SPP1(+) macrophages

Henriques A, Salvany-Celades M, Nieto P et al. · Nature genetics 2025 · PMID 41203813 · doi:10.1038/s41588-025-02380-2

This dataset

Open GSE272376 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 GSE272376_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 PRJNA1136536 and SRA study SRP520288. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41203813) ↗

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

GSM8399654 1010_2024-LY
GSM8399655 1011_2024-LY + PDL1
GSM8399656 1013_2024-LY
GSM8399657 1014_2024-LY + PDL1
GSM8399658 1015_2024-LY
GSM8399659 1017_2024-Veh
GSM8399660 1018_2024-Veh + PDL1
GSM8399661 1019_2024-Veh + PDL1
GSM8399662 1020_2024-Veh
GSM8399663 1021_2024-Veh
GSM8399664 1023_2024-LY + PDL1
GSM8399665 1025_2024-Veh + PDL1

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GSE301299 Multi-omics analysis identifies intrinsic Trp53 driven metastatic breast cancer subtypes [RNA-seq] 51 samples shares metastatic, driven
GSE313249 A Glucocorticoid-Fas axis controls immune evasion during metastatic seeding [RNAseq_4T1-tdTomato] 30 samples shares metastatic, controls
GSE303692 A plastic EMP1⁺ to LGR5⁺ cell state conversion as a therapeutic bypass to KRAS-G12D inhibition in metastatic colorectal cancer [RNA-Seq] 24 samples shares metastatic, colorectal
GSE294822 A plastic EMP1⁺ to LGR5⁺ cell state conversion as a therapeutic bypass to KRAS-G12D inhibition in metastatic colorectal cancer [SLAM-Seq] 15 samples shares metastatic, colorectal

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