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IFN-III primes pDCs for TLR7 activation and antagonizes TGF-β mediated-immune suppression in tumors.

GSE237879 Homo sapiens (human) RNA-seq (gene expression) 28 samples Submitted 2025/01/08 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 28 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
Homo sapiens (human)
Samples
28 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)
Conventional dendritic cell (cDC1, cDC2) and plasmacytoid dendritic cell (pDCs) subsets have specialized functions that can be modulated by the tumor microenvironment (TME). These cells produce different interferons that are central to antitumor immune responses. While the role of Type I Interferons (IFN-I) in tumor immunity is well characterized, the role of Type III interferons (IFN-III) produced by cDC1 in the TME and associated with good outcome remains completely unknown.
Read the full summary ↓
Here, we demonstrate that IFN-III orchestrates pDCs survival, activation and TLR7 expression in the blood and in tumors, enhancing their capacity to respond to TLR7-ligand. Importantly, IFN-III prevents the inhibition of pDCs induced by the TME or by TGF-β, a dominant TME inhibitory cue, and restores their production of IFN-⍺. Because of the essential role of TGF-β in immune regulation, this mechanism is expected to impact other pathological situations.
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 GSE237879_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: 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 PRJNA996983 and SRA study SRP450605. Searching any of these in the dataset finder brings you back here.

Samples in this study

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