Evidence map›Paper›PMID 40894279›Full record

ArticleCurrent urology2025

Unleashing the potential of urine DNA methylation detection: Advancements in biomarkers, clinical applications, and emerging technologies.

Xun Sun, Delin Wang, Shanhua Zhang, Jianyu Wang, Hao Ning, Haihu Wu, Fei Wu, Dongqi Tang, Jiaju Lyu

Abstract read
In one paragraph

Article in Current urology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

9 authors.

Xun SunCheeloo College of Medicine, Shandong University, Jinan, China.
Delin WangDepartment of Urology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Shanhua ZhangCheeloo College of Medicine, Shandong University, Jinan, China.
Jianyu WangDepartment of Urology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Hao NingDepartment of Urology, Shandong Provincial Hospital, Shandong University, Jinan, China.
Haihu WuDepartment of Urology, Shandong Provincial Hospital, Shandong University, Jinan, China.
Fei WuDepartment of Urology, Shandong Provincial Hospital, Shandong University, Jinan, China.
Dongqi TangCheeloo College of Medicine, Shandong University, Jinan, China.
Jiaju LyuCheeloo College of Medicine, Shandong University, Jinan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, the detection urinary DNA methylation in bladder cancer has witnessed significant advancements. Important breakthroughs have been achieved in the diagnosis of bladder cancer through the use of DNA methylation biomarkers in urine. Several clinical studies have successfully established multiple biomarkers and developed reliable diagnostic models. Additionally, certain assay kits are certified by the Food and Drug Administration or the National Medical Products Administration and provide dependable tools for clinical applications. However, traditional techniques have limitations in terms of sample requirements, operational complexity, and stability. This review presents the application of novel technologies for the detection of urinary DNA methylation in bladder cancer, including microfluidic, digital polymerase chain reaction, and CRISPR technologies. The introduction of these innovative approaches holds promise for enhancing the early diagnosis and prognosis of bladder cancer. These advances are expected to drive further research and clinical applications in this field.

Indexed as

Bladder cancerDigital PCRDNA methylationMicrofluidicsUrine

Identifiers

PMID40894279
PMCPMC12398378

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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.