Evidence map›Paper›PMID 42368666›Full record

ReviewCurrent urology2026

Advancements in delivery systems for in vivo chimeric antigen receptor T-cell therapy in urological diseases.

Yuxiao Li, Wen Zhang, Dongqi Tang

Abstract readReview
In one paragraph

Review in Current urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yuxiao LiInstitute of Medical Sciences, The Second Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China.
Wen ZhangInstitute of Medical Sciences, The Second Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China.
Dongqi TangInstitute of Medical Sciences, The Second Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chimeric antigen receptor (CAR) T-cell therapy is a new type of highly precise and targeted immunotherapy for urological diseases. It has demonstrated significant therapeutic potential in chronic and autoimmune kidney diseases such as renal fibrosis and membranous nephropathy. However, owing to its high cost, low efficiency, and serious side effects, such as cytokine storm syndrome, a new generation of drugs has emerged to solve these problems. In vivo CAR T-cell therapy is a treatment method that directly modifies specific cells within the patient's body through various delivery systems. Nonviral vectors (nanoparticles and exosomes) and viral vectors (adeno-associated viruses and lentiviruses) can be engineered to achieve better therapeutic effects. By taking advantage of different delivery systems and minimizing their drawbacks, in vivo CAR T-cell therapy can improve the stability and targeting ability, reduce immunogenicity, and minimize side effects. This review summarizes the mechanisms of action and clinical applications of various delivery systems used in in vivo CAR T-cell therapy, highlighting their potential in the treatment of urological diseases. Through a deeper understanding of the construction and optimization of well-designed platforms, the development of optimal delivery systems has valuable implications for the establishment of new pharmaceuticals for in vivo CAR T-cell therapy in urological diseases.

Indexed as

Delivery systemsGene therapyImmunotherapyIn vivo chimeric antigen receptor t-cell therapyUrological diseases

Identifiers

PMID42368666
PMCPMC13308914

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.