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The glutamate receptor antagonist ifenprodil inhibits hepatitis E virus infection

GSE274780 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/09/30 Platform GPL18573
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: 12 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
Modeling extrahepatic hepatitis E virus infection in induced human primary neuronsProceedings of the National Academy of Sciences of the United States of America · 2024
Summary (written by the submitters)
Infection with hepatitis E virus (HEV) represents a global problem, with over 20 million people infected annually. No specific antiviral drugs are available for treating HEV infection, necessitating the development of novel targeted therapeutics. Here, we report that the N-methyl-D-aspartate receptor (NMDAR) antagonist ifenprodil, a clinically approved drug used to treat idiopathic pulmonary fibrosis (IPF), is an HEV inhibitor in liver-derived cells.
Read the full summary ↓
In vitro investigation demonstrates that ifenprodil suppresses viral protein expression in a dose-dependent manner in human hepatoma cells by inhibiting early stages of viral infection. We also found that ifenprodil modulates host cell intrinsic biological processes distinct from virus-induced innate immunity, inhibiting HEV RNA accumulation in primary human hepatocytes. Finally, the inhibitory effect of ifenprodil in vivo was also tested in rabbits challenged with the HEV-3ra CHN-BJ-R14 strain. Fecal virus shedding was below the limit of detection in two animals for both ribavirin-treated and ifenprodil-treated rabbits compared to vehicle-treated control animals. Our data demonstrate that ifenprodil is an effective anti-HEV compound with potential as a therapeutic candidate for the treatment of HEV infection.
Published in
Modeling extrahepatic hepatitis E virus infection in induced human primary neurons
Jagst M, Gömer A, Augustyniak S et al. · Proceedings of the National Academy of Sciences of the United States of America 2024 · PMID 39546567 · doi:10.1073/pnas.2411434121
This dataset
Open GSE274780 in finder → Find more human 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 GSE274780_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 PRJNA1148036 and SRA study SRP526289. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39546567) ↗
Study design
12 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 12 sample titles: 12 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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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.