Evidence map›Paper›PMID 39366385›Full record

ReviewCell reports. Medicine2024

Gene therapy for chronic pain management.

Yi-Ze Li, Ru-Rong Ji

Abstract readReview
In one paragraph

Review in Cell reports. Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 citing papers in PubMed.

  1. Article
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  9. Targeting NaInternational journal of molecular sciences · 2026
    Review
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  12. Article
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  18. Emerging role of macrophages in neuropathic pain.Journal of orthopaedic translation · 2025
    Review
  19. Article
  20. 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

2 authors.

Yi-Ze LiCenter for Translational Pain Medicine, Department of Anesthesiology, Duke University Medical Center, Durham, NC 27710, USA.
Ru-Rong JiCenter for Translational Pain Medicine, Department of Anesthesiology, Duke University Medical Center, Durham, NC 27710, USA; Departments of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA; Departments of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA. Electronic address: ru-rong.ji@duke.edu.

Funding

Targeting checkpoint inhibitors for pain controlRF1NS131812 · NINDS · DUKE UNIVERSITY · PI RU-RONG JI · 2023 to 2026
$4.4M
NINDS NIH HHS RF1 NS131812
6 · The paper itself

Abstract

Despite significant advances in identifying molecular targets for chronic pain over the past two decades, many remain difficult to target with traditional methods. Gene therapies such as antisense oligonucleotides (ASOs), RNA interference (RNAi), CRISPR, and virus-based delivery systems have played crucial roles in discovering and validating new pain targets. While there has been a surge in gene therapy-based clinical trials, those focusing on pain as the primary outcome remain uncommon. This review examines various gene therapy strategies, including ASOs, small interfering RNA (siRNAs), optogenetics, chemogenetics, and CRISPR, and their delivery methods targeting primary sensory neurons and non-neuronal cells, including glia and chondrocytes. We also explore emerging gene therapy tools and highlight gene therapy's clinical potential in pain management, including trials targeting pain-related diseases. Advances in single-cell analysis of sensory neurons and non-neuronal cells, along with the development of new delivery tools, are poised to accelerate the application of gene therapy in pain medicine.

Indexed as

Chronic PainGenetic TherapyPain ManagementAnimalsHumansOligonucleotides, AntisenseOptogeneticsRNA, Small InterferingSensory Receptor CellsOligonucleotides, AntisenseRNA, Small Interfering

Identifiers

PMID39366385
PMCPMC11513853

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.