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Synthetic RIG-I agonist-mediated cancer immunotherapy synergizes with MAP-Kinase inhibition against BRAF mutated melanoma [YUMM1.7]

GSE269008 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2024/06/04 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 15 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
15 samples: 15 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
Synthetic RIG-I agonist-mediated cancer immunotherapy synergizes with MAP kinase inhibition against BRAF-mutated melanomaMolecular therapy. Nucleic acids · 2024
Summary (written by the submitters)
The implementations of targeted molecular therapies and immunotherapy in melanoma vastly improved the therapeutic outcome in patients with limited efficacy of surgical intervention. Nevertheless, a large fraction of melanoma patients still remains refractory or acquires resistance to these new forms of treatment, illustrating a need for improvement.
Read the full summary ↓
Here we report that the clinically relevant combination of MAP kinase inhibitors Dabrafenib and Trametinib synergizes with RIG-I agonist-induced immunotherapy to kill BRAF-mutated human and mouse melanoma cells. Kinase inhibition did not compromise the agonist-induced innate immune response of the RIG-I pathway in host immune cells. In a melanoma transplantation mouse model, the triple therapy outperformed the individual therapies. Our study suggests that targeted activation of RIG-I with its synthetic ligand 3pRNA could vastly improve tumor control in a substantial fraction of melanoma patients receiving MAP kinase inhibitors.
Published in
Synthetic RIG-I agonist-mediated cancer immunotherapy synergizes with MAP kinase inhibition against BRAF-mutated melanoma
Grützner C, Tan YP, Müller P et al. · Molecular therapy. Nucleic acids 2024 · PMID 39165562 · doi:10.1016/j.omtn.2024.102283
This dataset
Open GSE269008 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 GSE269008_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 PRJNA1119955 and SRA study SRP511603. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39165562) ↗
Study design
15 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 15 sample titles: 15 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
Datasets on a similar topic

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