October 25, 2024
Bladder cancer is one of the most common cancers in Canada and early detection is vital to improving treatment and survival rates. Currently, a method called urine cytology is used to check for cancer cells in urine. However, this process has some drawbacks: it can be subjective, takes time to get results and is quite costly.
That’s where a new collaborative research project led by Dr. Tao Huan at the University of British Columbia and Dr. Gang Wang at the BC Cancer Pathology Department comes in. The team is using advanced technology called mass spectrometry to study metabolites found in urine samples. Metabolites are tiny molecules that can offer clues about what’s happening in the body. By comparing the metabolites in people with bladder cancer to those in healthy individuals, the researchers hope to find unique patterns, or “biomarkers,” that signal the presence of cancer.
On top of that, the team will consider risk factors such as smoking, age, sex, exposure to certain chemicals and family history. Using this information, they aim to develop a machine-learning model that could accurately predict who might have bladder cancer, potentially leading to a simple, effective urine test.
Discovering a biomarker would be a breakthrough that could significantly improve the way bladder cancer is diagnosed, allowing for quicker treatment and better outcomes, all while reducing healthcare costs. It’s an exciting development that could benefit many patients across the country.
Did you know British Columbia’s unique contributions to scientific advancements like this are helping to revolutionize cancer care?
At this year’s Don Rix Distinguished Keynote Address, Dr. Sam Aparicio will dive deeper into the cutting-edge research reshaping cancer diagnosis and treatment. Register now to be part of the conversation shaping the future of oncology!