GEO series

Histamine H4 receptor antagonists prevent receptor-mediated and EBV-induced B cell proliferation [ATAC-seq]

GSE300663 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2026/06/29 Platform GPL18573

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 20 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism: Homo sapiens (human)
Samples: 20 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.
Paper: A subset of histamine H4 receptor antagonists prevents B lymphocyte proliferation induced by BCR/TLR9 engagement or EBV infectionAntiviral research · 2026

Summary (written by the submitters)

Epstein-Barr virus (EBV) infects over 90% of the global population and establishes lifelong latency in memory B cells. In healthy individuals, this latent infection is typically kept in check by the immune system. However, in immunosuppressed patients, EBV can reactivate, leading to uncontrolled B cell proliferation and development of post-transplant lymphoproliferative disorders (PTLD)—a potentially fatal complication.

Read the full summary ↓

In this study, we demonstrate that selective antagonists of the histamine H4 receptor (H4R), a G protein-coupled receptor expressed in immune cells, potently suppress B cell activation and proliferation triggered by antigenic stimuli or EBV infection. Notably, the lead compound A943931 inhibited transcriptional programs critical for B cell activation, including downregulation of key metabolic genes, resulting in profound suppression of both glycolysis and oxidative phosphorylation. A943931 also blocked EBV-driven B cell immortalization and impaired energy metabolism in lymphoblastoid cell lines, albeit to a lesser extent than in receptor-stimulated B cells. In vivo, A943931 suppressed tumor growth in Daudi Burkitt lymphoma xenografts and prevented B cell lymphoma development in EBV-infected humanized mice. These findings reveal a novel immunometabolic vulnerability of EBV-infected B cells and position H4R antagonists as promising therapeutic candidates for EBV-associated lymphoproliferative disorders, including PTLD and potentially EBV-linked autoimmune diseases.

Published in

A subset of histamine H4 receptor antagonists prevents B lymphocyte proliferation induced by BCR/TLR9 engagement or EBV infection

Roy M, Bardel E, Gromolard L et al. · Antiviral research 2026 · PMID 42140525 · doi:10.1016/j.antiviral.2026.106438

This dataset

Open GSE300663 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE300663_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1281623 and SRA study SRP594291. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42140525) ↗

Samples in this study

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+ 20 more — browse all 20 samples with per-sample file links →

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