Evidence map›Paper›PMID 41418774›Full record

ReviewCell reports. Medicine2026

Emerging trends in gene and cell therapy: CRISPR in DNA editing and beyond.

Ruijin Ji, Qiubing Chen, Ying Zhang

Abstract readReview
In one paragraph

Review in Cell reports. Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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  6. 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

3 authors.

Ruijin JiDepartment of Rheumatology and Immunology, Medical Research Institute, Frontier Science Center for Immunology and Metabolism, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China.
Qiubing ChenDepartment of Rheumatology and Immunology, Medical Research Institute, Frontier Science Center for Immunology and Metabolism, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China.
Ying ZhangDepartment of Rheumatology and Immunology, Medical Research Institute, Frontier Science Center for Immunology and Metabolism, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China; Department of Esophagus, Mediastinum and Lymphatic Oncology, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan, China; TaiKang Centre for Life and Medical Sciences, Wuhan University, Wuhan, China; State Key Laboratory of Virology and Biosafety, Wuhan University, Wuhan, China. Electronic address: ying.zhang84@whu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

CRISPR-based gene and cell therapies are rapidly transitioning from experimental platforms to clinical reality, exemplified by the recent approval of CRISPR-derived treatments for β-hemoglobinopathies. This review highlights how advances in genome editing technologies, ranging from CRISPR-Cas nucleases to base and prime editors, are expanding the therapeutic landscape beyond traditional gene knockout approaches. We focus on the clinical translation of these tools, drawing on examples from ongoing and completed human trials to illustrate their potential across diverse disease areas. Furthermore, we discuss critical considerations such as delivery challenges, long-term safety, immune responses, and editing specificity, all of which are critical to the safe and effective integration of CRISPR technologies into modern medicine.

Indexed as

Cell- and Tissue-Based TherapyClustered Regularly Interspaced Short Palindromic RepeatsCRISPR-Cas SystemsGene EditingGenetic TherapyAnimalsHumanscell therapyCRISPRgene therapygenome editingRNA editing

Identifiers

PMID41418774
PMCPMC12866100

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.