Catching cancer in its early stages is one of the most effective methods doctors have of improving patients’ survival rates. However, this can be difficult as many of the screening tests in current use are type-specific. This means that patients need to take separate tests to check for each type of cancer they are at risk of.
Projects are currently underway to develop multi-cancer early detection (MCED) tests, but most of these focus on screening for DNA shed from tumours and a have limited ability to detect cancerous cells that form during the earliest stages of the disease.
Now, researchers from Chalmers University of Technology, Sweden, have developed a simple MCED blood or urine test using machine learning algorithms that can accurately detect 14 different stage 1 cancers. Instead of searching for DNA from tumours, it looks for changes in metabolic sugars called glycosaminoglycans known to be caused by cancerous cells.
In a study involving more than 1,250 participants, both healthy and previously diagnosed with cancer, the researchers found that the test could accurately detect multiple cancers, including kidney and brain tumours. It was also twice as effective as DNA-based MCED tests in detecting stage 1 cancers in asymptomatic healthy people.
"This is a ground-breaking study that gives us hope that one day society will be able to create screening programmes that can detect all cancer types early,” said study author Francesco Gatto, a visiting researcher at the Department of Biology and Biological Engineering at Chalmers.
“The method makes it possible to find cancer types that are not screened for today and cannot be found with DNA-based MCED tests, such as brain tumours and kidney cancer.
"The fact that the method is comparatively simple means that the cost will be significantly low, ultimately enabling more people to have access to and take the test.”
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