← BioTransfer GEO Dataset Finder
GEO series

Histamine H4 receptor antagonists prevent receptor-mediated and EBV-induced B cell proliferation [RNA-Seq]

GSE300055 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/12/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × unstimulated CD19⁺ B cells, DMSO control vs 3 × unstimulated CD19⁺ B cells, A943931 treatment vs 3 × stimulated CD19⁺ B cells, DMSO control vs 3 × stimulated CD19⁺ B cells, A943931 treatmentGroups 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.
Summary (written by the submitters)
Epstein-Barr virus (EBV) infects over 90% of individuals worldwide and establishes lifelong latency in memory B cells. While this latency is typically controlled by the immune system in healthy people, it can reactivate leading to cell immortalization and post-transplant lymphoproliferative disorders (PTLD), a frequent and potentially life-threatening condition in immunosuppressed patients.
Read the full summary ↓
Surprisingly, we show that specific antagonists of the histamine H4 receptor (H4R), a G protein-coupled receptor expressed in immune cells, prevent the activation and proliferation of B cells following antigenic-like stimulation (BCR, TLR9, or CD40 ligands) or EBV infection. The lead compound, A943931, inhibited transcriptional but not epigenetic programs associated with B cell activation. Key metabolic genes, were downregulated, with a marked inhibition of glycolysis and oxidative phosphorylation. EBV-driven B cell immortalization was also blocked by H4R antagonists. A943931 similarly impaired energy production in lymphoblastoid cell lines, albeit to a lesser extent than in receptors-stimulated B cells. Finally, A943931 inhibited the growth of the Burkitt lymphoma Daudi xenografted in NSG mice and the development of B cell lymphoma in EBV-infected humanized mice. These findings highlight promising therapeutic potential of some H4R antagonists for EBV-induced lymphoproliferations such as PTLD and, more broadly, for EBV-linked autoimmune disorders.
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 GSE300055_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 PRJNA1278758 and SRA study SRP592658. Searching any of these in the dataset finder brings you back here.

Study design
3 × unstimulated CD19⁺ B cells, DMSO control vs 3 × unstimulated CD19⁺ B cells, A943931 treatment vs 3 × stimulated CD19⁺ B cells, DMSO control vs 3 × stimulated CD19⁺ B cells, A943931 treatment

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
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.