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Metabolic inhibition of glutamate-cysteine ligase increases dendritic cell-mediated anti-tumor immunity in melanoma

GSE329033 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2026/07/01 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 20 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
20 samples: 5 × tg(Grm1)Epv, BSO+DC boost, vs 5 × tg(Grm1)Epv, DC boost, vs 5 × tg(Grm1)Epv, BSO, vs 5 × tg(Grm1)Epv, PBS,Groups 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
Metabolic inhibition of glutamate-cysteine ligase increases dendritic cell-mediated antitumor immunity in melanomaJournal for immunotherapy of cancer · 2026
Summary (written by the submitters)
Metabolic competition and nutrient restriction in the tumor microenvironment (TME) shape the immune infiltrate in tumors and subsequently tumor immunity. In this study we used the transgenic melanoma mouse model tg(Grm1)EPv, which spontaneously develops melanoma due to the ectopic expression of the metabotropic glutamate receptor 1 (Grm1) in melanocytes to investigate if aberrant glutamate metabolism drives tumor formation, and affects immune cell function.
Read the full summary ↓
LC-MS/MS-based metabolomic analyses and RNA sequencing revealed changes in glutaminolysis, a glycolytic shift (Warburg effect), and reduced ATP levels in advanced tumors compared with tumor free tissue, suggesting respiratory chain dysfunction. These metabolic changes in the TME are advantageous for the tumor cells and unfavorable for immune cells, such as dendritic cells (DC). Indeed, flow cytometry analysis of myeloid subsets during tumor progression showed a decline in tumor-infiltrating conventional type 2 dendritic cell (cDC2) and macrophages, alongside an increase in neutrophil and monocyte populations in advanced lesions. Interference with glutaminolysis using L-buthionine sulfoximine (BSO), an inhibitor of the glutamylcysteine synthetase depleting cellular glutathione levels, induced immunogenic cell death, namely ferroptosis, in an tg(Grm1)EPv -derived cell line in vitro. Therefore, we evaluated the combination of this inhibitor with immunotherapy as a promising new approach for the treatment of tumors in the tg(Grm1)EPv mouse model. We observed that tumor growth could be delayed in vivo when BSO was combined with a therapy regimen boosting DC numbers and activation. This knowledge can drive the design of novel therapeutic strategies for cancer patients involving potential modification of tumor glutamate metabolism.
Published in
Metabolic inhibition of glutamate-cysteine ligase increases dendritic cell-mediated antitumor immunity in melanoma
Dieckmann SM, Tripp CH, Strandt H et al. · Journal for immunotherapy of cancer 2026 · PMID 42379703 · doi:10.1136/jitc-2026-014808
This dataset
Open GSE329033 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 GSE329033_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 PRJNA1457426 and SRA study SRP694546. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42379703) ↗
Study design
5 × tg(Grm1)Epv, BSO+DC boost, vs 5 × tg(Grm1)Epv, DC boost, vs 5 × tg(Grm1)Epv, BSO, vs 5 × tg(Grm1)Epv, PBS,

Supports a between-group comparison across 20 samples.

How we read this: 4 replicated groups read from 20 sample titles; they account for 20 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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