Evidence map›Paper›PMID 40790606›Full record

ArticleClinical epigenetics2025

Detection of genome-wide methylation changes in bladder cancer by long-read sequencing of urinary DNA.

Anshita Goel, Benjamin J Tura, Joanne D Stockton, Nicholas Tovey, Luke Ames, Andrew D Beggs, Maurice P Zeegers, Nicholas D James, K K Cheng, Richard T Bryan and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical epigenetics, 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. Review
  2. Review
  3. Translational andrology and urology · 2026
    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

12 authors.

Anshita GoelThe Bladder Cancer Research Centre, Department of Cancer and Genomic Sciences, College of Medicine and Health, University of Birmingham, Birmingham, B15 2TT, UK.
Benjamin J TuraThe Bladder Cancer Research Centre, Department of Cancer and Genomic Sciences, College of Medicine and Health, University of Birmingham, Birmingham, B15 2TT, UK.
Joanne D StocktonGenomics Birmingham, College of Medicine and Health, University of Birmingham, Birmingham, B15 2TT, UK.
Nicholas ToveyGenomics Birmingham, College of Medicine and Health, University of Birmingham, Birmingham, B15 2TT, UK.
Luke AmesGenomics Birmingham, College of Medicine and Health, University of Birmingham, Birmingham, B15 2TT, UK.
Andrew D BeggsGenomics Birmingham, College of Medicine and Health, University of Birmingham, Birmingham, B15 2TT, UK.
Maurice P ZeegersDepartment of Epidemiology, School of Nutrition and Translational Research in Metabolism, University of Maastricht, Maastricht, The Netherlands.
Nicholas D JamesThe Institute of Cancer Research, London, SM2 5NG, UK.
K K ChengDepartment of Applied Health Sciences, College of Medicine and Health, University of Birmingham, Birmingham, B15 2TT, UK.
Richard T BryanThe Bladder Cancer Research Centre, Department of Cancer and Genomic Sciences, College of Medicine and Health, University of Birmingham, Birmingham, B15 2TT, UK.
Douglas G WardThe Bladder Cancer Research Centre, Department of Cancer and Genomic Sciences, College of Medicine and Health, University of Birmingham, Birmingham, B15 2TT, UK. d.g.ward@bham.ac.uk.
Roland ArnoldThe Bladder Cancer Research Centre, Department of Cancer and Genomic Sciences, College of Medicine and Health, University of Birmingham, Birmingham, B15 2TT, UK. r.arnold.2@bham.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNon-invasive urine tests for bladder cancer (BC) could reduce dependence on flexible cystoscopy for diagnosis and surveillance. Most recent developments in urine testing are based on targeted detection of genomic and/or epigenomic markers. We hypothesised that long-read whole-genome sequencing of urinary DNA with direct methylation profiling may allow accurate BC detection and insights into disease biology. However, the feasibility of such an approach has not yet been reported.

methodsWe applied long-read whole-genome sequencing with direct methylation detection to urine cell pellet DNA (ucpDNA) from 21 haematuria clinic patients: 13 BCs and 8 non-BCs. The modkit Hidden Markov Model algorithm was used to define differentially methylated regions across the genome. The ability to discriminate between BC and non-BC, and the cellular pathways affected were tested using PCA, h-clust and GSEA.

resultsWe observed global hypomethylation and cancer-specific patterns of promoter hypermethylation in urine from BC patients. Sequencing of a single ucpDNA sample per flow cell yielded read depths of 18-34x; furthermore, BC methylation patterns were also evident with 2-5x multiplex sequencing. Copy number changes were also evident in ucpDNAs from BC patients. A limitation of the study is the small number of samples analysed; however, the detection of cancer-specific events demonstrates the feasibility of the approach, both in single and multiplexed flow-cell runs.

conclusionsEven at low-read depths, genome-wide methylation patterns in urinary DNA reflect the presence of BC, potentially permitting rapid, non-invasive and cost-effective BC detection.

Indexed as

DNA MethylationUrinary Bladder NeoplasmsWhole Genome SequencingAgedAged, 80 and overBiomarkers, TumorFemaleHumansMaleMiddle AgedPromoter Regions, GeneticSequence Analysis, DNABiomarkers, TumorBladder cancerLong-read sequencingMethylationNanoporeUrine DNA

Identifiers

PMID40790606
PMCPMC12337379

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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.