Evidence map›Paper›PMID 39759876›Full record

ArticleMolecular therapy. Nucleic acids2025

A sort and sequence approach to dissect heterogeneity of response to a self-amplifying RNA vector in a novel human muscle cell line.

Rachel D Barton, John S Tregoning, Ziyin Wang, Daniel Gonçalves-Carneiro, Radhika Patel, Paul F McKay, Robin J Shattock

Abstract read
In one paragraph

Article in Molecular therapy. Nucleic acids, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Immunology of RNA-based vaccines: The critical interplay between inflammation and expression.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Rachel D BartonDepartment of Infectious Disease, Imperial College London, London W2 1PG, UK.
John S TregoningDepartment of Infectious Disease, Imperial College London, London W2 1PG, UK.
Ziyin WangDepartment of Infectious Disease, Imperial College London, London W2 1PG, UK.
Daniel Gonçalves-CarneiroDepartment of Infectious Disease, Imperial College London, London W2 1PG, UK.
Radhika PatelNational Heart and Lung Institute, Imperial College London, London W2 1PG, UK.
Paul F McKayDepartment of Infectious Disease, Imperial College London, London W2 1PG, UK.
Robin J ShattockDepartment of Infectious Disease, Imperial College London, London W2 1PG, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Self-amplifying RNA (saRNA) is an extremely promising platform because it can produce more protein for less RNA. We used a sort and sequence approach to identify host cell factors associated with transgene expression from saRNA; the hypothesis was that cells with different expression levels would have different transcriptomes. We tested this in CDK4/hTERT immortalized human muscle cells transfected with Venezuelan equine encephalitis virus (VEEV)-derived saRNA encoding GFP. Cells with the highest expression levels had very high levels of transgene mRNA (5%-10% total reads); the cells sorted with low and negative levels of GFP protein also had detectable levels of both VEEV and GFP RNA. To understand host responses, we performed RNA sequencing. Differentially expressed gene (DEG) patterns varied with GFP expression; GFP high cells had many more DEGs, which were associated with protein synthesis and cell metabolism. Comparing profiles by an unsupervised approach revealed that negative cells expressed higher levels of cell-intrinsic immunity genes such as

Indexed as

alphavirusexpressioninnate immunityMT: Delivery StrategiesRNAself-amplifyingvaccine

Identifiers

PMID39759876
PMCPMC11700297

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.