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Tryptophan 2, 3-dioxygenase positive matrix fibroblasts fuel breast cancer lung metastasis via kynurenine-mediated ferroptosis resistance of metastatic cells and T cell dysfunction II

GSE270152 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2024/06/21 Platform GPL30215

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 × N_MF vs 3 × N_Myo vs 3 × M_MF vs 3 × M_MyoGroups 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.

Summary (written by the submitters)

Background: Tumor metastasis is a major threat to cancer patient survival. The organ-specific niche plays a pivotal role in tumor organotropic metastasis. Fibroblasts serve as a vital component of the metastatic microenvironment, but how heterogeneous metastasis-associated fibroblasts (MAFs) promote organotropic metastasis is poorly characterized.

Read the full summary ↓

Here, we aimed to decipher the heterogeneity of MAFs and elucidate the distinct roles of these fibroblasts in pulmonary metastasis formation in breast cancer. Methods: Mouse models of breast cancer pulmonary metastasis were established using an in vivo selection method of repeated injections of metastatic cells purified from the mouse lung. Single-cell RNA sequencing (scRNA-seq) was employed to investigate the heterogeneity of MAFs. Transgenic mice were used to examine the contribution of tryptophan 2, 3-dioxygenase positive matrix fibroblasts (TDO2+ MFs) in lung metastasis.. Results: We uncovered three subtypes of MAFs in the lung metastatic microenvironment and their transcriptome profiles changed dynamically as lung metastasis evolves. As the predominant subtype, matrix fibroblasts (MFs) were exclusively marked by platelet-derived growth factor receptor alpha (PDGFRA) and mainly located on the edge of the metastasis, and T cells were enriched around MFs. Notably, high MFs signatures were significantly associated with poor survival in breast cancer patients. Lung metastases were markedly diminished and the suppression of T cells was dramatically attenuated in MF-depleted experimental metastatic mouse models. We found that TDO2+ MFs control pulmonary metastasis by producing kynurenine (KYN), which upregulated FTH1 level in disseminated tumor cells (DTCs), enabling DTCs to resist ferroptosis. Moreover, TDO2+ MFs-secreted the chemokines CCL8 and CCL11 recruited T cells. TDO2+ MF-derived KYN induced T cell dysfunction. Conditional knockout of Tdo2 in MFs diminished lung metastasis and enhanced immune activation. Conclusions: Our study reveals crucial roles of TDO2+ MFs in promoting lung metastasis and DTCs' immune evasion in the metastatic niche. It suggests that targeting the metabolism of lung-specific stromal cells may be an effective treatment strategy for breast cancer patients with lung metastasis.

This dataset

Open GSE270152 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 GSE270152_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 PRJNA1125348 and SRA study SRP514659. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × N_MF vs 3 × N_Myo vs 3 × M_MF vs 3 × M_Myo

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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

GSM8335644 N_MF1 N_MF
GSM8335645 N_MF2 N_MF
GSM8335646 N_MF3 N_MF
GSM8335647 N_Myo1 N_Myo
GSM8335648 N_Myo2 N_Myo
GSM8335649 N_Myo3 N_Myo
GSM8335650 M_MF1 M_MF
GSM8335651 M_MF2 M_MF
GSM8335652 M_MF3 M_MF
GSM8335653 M_Myo1 M_Myo
GSM8335654 M_Myo2 M_Myo
GSM8335655 M_Myo3 M_Myo

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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.