← BioTransfer GEO Dataset Finder
GEO series

Tryptophan metabolism drives dynamic immunosuppressive myeloid states in IDH-mutant gliomas [scRNA-Seq]

GSE166218 Mus musculus (mouse) Single-cell RNA-seq 64 samples Submitted 2021/03/04 Platform GPL24247Platform GPL21103
At a glance

Single-cell RNA-seq · mouse · 64 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Mus musculus (mouse)
Samples
64 samples
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)
Intratumoral microglia and MΦ constitute up to 70% of the tumor mass of high-grade gliomas (HGG) with profound impact on hallmarks of malignancy such as angiogenesis and immunosuppression. The dynamics and functional states of intratumoral myeloid cells during tumor progression and the molecular mechanisms controlling them are poorly understood.
Read the full summary ↓
Here we define homeostatic and antigen-presenting myeloid cellular states in experimental and human HGG by longitudinal single-cell RNA-sequencing and combined transcriptome and proteome profiling. During glioma progression, myeloid cells gradually shift from a homeostatic to a tumor-associated effector state. We show that these dynamics are under strict control by early changes in resident microglia and the tumor genotype: In gliomas with mutations in isocitrate dehydrogenase (IDH), a disease-defining driver mutation, differentiation of invaded myeloid cells was blocked resulting in an immature, immunosuppressive phenotype. In late-stage IDH-mutant gliomas, monocyte-derived MΦ drive a tolerogenic remodeling of the glioma microenvironment thus preventing T-cell response. We define the molecular mechanism responsible for the tumor genotype-dependent education of infiltrating MΦ to be causally related to an enzymatically enhanced tryptophan catabolism via TDO2, resulting in the production of kynurenine, an endogenous ligand of the aryl hydrocarbon receptor (AHR). TDO2 activation further induces an amino acid starvation response triggering the import of exogenous tryptophan by intratumoral MΦ via LAT1-CD98. We here provide evidence that paracrine R-2-HG and tryptophan are critically involved in the differentiation and activation of monocyte-derived MΦ and that the previously observed altered amino acid metabolism in IDHmut gliomas is also responsible for shaping an immunosuppressive tumor microenvironment through maintenance of this complex metabolic axis. We further show that this regulatory metabolic network is particularly active in infiltrating MΦ because of their distinct expression profile that constitutes an immune subset-specific metabolic vulnerability. Consequently, the immunosuppressive phenotype in IDH-mutant glioma models was reversed by pharmacological inhibition of LAT1-CD98 or AHR. Thus, we provide evidence for a tumor genotype-dependent, dynamic network of resident and recruited intratumoral myeloid cells that shape the immune microenvironment of IDH-mutant HGG through pleiotropic interaction with the tumor metabolome and identify tryptophan metabolism as a viable therapeutic target for the immunotherapy of IDH-mutant tumors.
This dataset
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.

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 GSE166218_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA699601 and SRA study SRP304784. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 64 more — browse all 64 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.