Innovative Urine Test Detects Bladder Cancer Through Tumor DNA Analysis

Researchers at the University of Birmingham’s Bladder Cancer Research Center have developed a groundbreaking method to identify bladder cancer by analyzing DNA methylation patterns in urine samples. This approach focuses on detecting epigenetic modifications—specifically methylation changes—that occur across the entire length of DNA in urine. Unlike existing tests, such as the GALEAS bladder test, which analyze small DNA segments, this new technique utilizes advanced long-read sequencing technology to map genome-wide methylation patterns.

The study demonstrates that even when urine samples contain a mixture of healthy and cancerous cell DNA, the method can reliably distinguish cancer cases from non-cancer cases, even at low tumor DNA levels. This indicates a potential for early detection, which could revolutionize bladder cancer diagnostics. By providing a comprehensive view of epigenetic alterations associated with tumors, the method could aid in developing next-generation urine tests that not only detect cancer but also reveal additional tumor features.

Professor Rik Bryan highlights that these findings open up new questions and possibilities in cancer research. The long-read sequencing approach may enable researchers to understand the earliest changes in bladder tissue that lead to tumor development, paving the way for earlier diagnosis and better treatment strategies.

Dr. Anshita Goel, a bioinformatics researcher involved in the project, emphasizes that this proof-of-concept could lead to a clinical test that is non-invasive, cost-effective, and more informative than current methods—using only urine samples and modern sequencing technology. The extensive data generated will also help develop artificial intelligence tools to categorize patients based on their methylation patterns, ultimately guiding personalized treatment plans.

Published in Clinical Epigenetics, this innovative research signifies a major step forward in non-invasive cancer detection, with the potential to improve patient outcomes through earlier and more accurate diagnosis.

Source: medicalxpress.com