Researchers from the University of Birmingham’s Bladder Cancer Research Center have used a new method to detect chemical changes in the DNA in an individual’s urine sample; epigenetic changes, called methylation.
Published in Clinical Epigenetics, these changes could be used to indicate the presence of bladder cancer.
While current state-of-the-art diagnostic urine tests, such as the team’s GALEAS Bladder test, are already very accurate and starting to be used in the UK’s National Health Service, they rely on the analysis (sequencing) of small segments of DNA.
The team’s new approach looks at methylation changes across the whole length of the DNA in a urine sample, the first study to map these patterns using a new DNA sequencing technology.
Even though patients’ urine samples contained DNA from both healthy and cancerous cells, the team was able to discriminate cancer from non-cancer patients, even if the tumor DNA level was low. This approach may form the basis of a next generation of diagnostic urine tests that could reveal additional features of tumor DNA, including those detected by the GALEAS Bladder test.
Professor Rik Bryan, Professor of Urothelial Cancer Research and Director of the Bladder Cancer Research Center at the University of Birmingham, said, “These are very interesting and exciting data, and as with all cancer research, our findings prompt a lot of new questions as well as answers.
“However, this long-read sequencing approach may allow us to better understand the very earliest changes in the bladder that ultimately lead to the development of a bladder tumor. In turn, that may then allow us to deliver a new type of urine test, but there is still a long way to go.”
Dr. Anshita Goel, Bioinformatic Research Fellow, said, “Our proof-of-concept study offers a glimpse of what could be achievable in a clinical setting: a comprehensive, non-invasive test that could surpass today’s clinical methods. With nothing more than a urine sample and cost-effective sequencing technology, we can uncover the hidden epigenetic signatures of bladder cancer—opening the door to faster, gentler, and more patient-friendly disease detection in the future.”
The data generated by the new approach is extensive, and the team is now starting to develop artificial intelligence methods that can classify patients based on their DNA methylation patterns, with the ultimate aim of directing them to the optimal treatment pathway.
More information:
Anshita Goel et al, Detection of genome-wide methylation changes in bladder cancer by long-read sequencing of urinary DNA, Clinical Epigenetics (2025). DOI: 10.1186/s13148-025-01946-5
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