← BioTransfer GEO Dataset Finder
GEO series

Interleukin-1β Induces Human Endothelial Surface Expression and Trans-presentation of Interleukin-15 by Relieving let-7c-3p Suppression of Protein Translation (bulk RNA-Seq)

GSE266372 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2024/09/30 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 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
Homo sapiens (human)
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
IL-1β Induces Human Endothelial Surface Expression of IL-15 by Relieving let-7c-3p Suppression of Protein TranslationJournal of immunology (Baltimore, Md. : 1950) · 2024
Summary (written by the submitters)
Expression of interleukin-15 (IL-15) on the surface of human graft endothelial cells (ECs) bound to the IL-15 receptor a (IL-15Ra) subunit can increase the activation of cytotoxic T lymphocytes (CTLs), potentiating allograft rejection. Our previous work showed that surface expression of this protein complex could be induced by alloantibody-mediated complement activation through increased IL-1b synthesis, secretion, and autocrine/paracrine IL-1-mediated activation of NF-kB.
Read the full summary ↓
Here we report that cultured human ECs express 8 differently spliced IL-15 transcripts. Remarkably, IL-1β does not alter the expression level of any IL-15 transcript but induces surface expression independently of RNA Polymerase II-mediated transcription while requiring new protein translation. Mechanistically, IL-1β causes an NF-kB-mediated reduction in the level of microRNA Let-7c-3p, thereby relieving a block of translation of IL-15 surface protein. Let7c-3p antimir can induce EC surface expression of IL-15/IL-15Ra in the absence of complement activation or of IL-1, enabling IL-15 trans-presentation to boost CD8 T cell activation. Because of the complexity we have uncovered in IL-15 regulation, we recommend caution in interpreting increased total IL-15 mRNA or protein levels as a surrogate for trans-presentation.
Published in
IL-1β Induces Human Endothelial Surface Expression of IL-15 by Relieving let-7c-3p Suppression of Protein Translation
Mullan CW, Summer L, Lopez-Giraldez F et al. · Journal of immunology (Baltimore, Md. : 1950) 2024 · PMID 39302113 · doi:10.4049/jimmunol.2400331
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 GSE266372_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 PRJNA1106841 and SRA study SRP505232. Searching any of these in the dataset finder brings you back here.

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

Search all human 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.