In the future, a bit of saliva may be enough to detect the budding cancer. Researchers at the University of Gothenburg have developed an efficient method for deciphering changes in sugar molecules in cancer cells. Glycans are structures of sugar molecules linked to proteins in cells. The structure of the glycan determines the function of the protein. It has long been known that changes in glycan structure can predict inflammation or disease in the body.
Now, researchers at the University of Gothenburg have developed a way to distinguish between different types of structural changes, which may provide a precise answer to disease-specific changes.
"We analyzed data from about 220 patients with 11 different diagnoses of cancer and found differences in the substructure of glycans across cancer types," said Daniel Bojar, associate senior lecturer in bioinformatics at the University of Gothenburg and first author of the study published in Cell Reports Methods. "We were able to find these connections by letting our newly developed method process large amounts of data with the help of artificial intelligence."
Other research groups study the substructure of sugars, looking for so-called biomarkers to characterize the problem. This often involves using mass spectrometry to perform statistical tests to find out whether levels of individual sugars are significantly higher or lower in cancer patients. The sensitivity of these tests is too low and unreliable because the different sugars are structurally related and therefore not independent of each other.
Daniel-Boyard's research team used a new method involving artificial intelligence that takes these issues into account and is able to find patterns in data sets where other methods fail.
"We can trust our results; they are statistically significant. If we know what we are looking for, it is easier to find the right results. Now, we will use these biomarkers to develop tests," says Daniel Bojar.
This fall, his research group received 4 million Swedish kronor from the Lundberg Foundation to purchase a state-of-the-art mass spectrometer. The instrument will serve as an artificial intelligence platform to support researchers studying sugars, such as those found in lung cancer samples. The idea is to detect cancer earlier, thus improving the chances of recovery.
"We want to develop a reliable, rapid assay to detect cancer and the type of cancer in a blood sample or saliva. I think we might be able to do clinical testing on human samples in 4-5 years," Daniel-Boyar said. "
Compiled source: ScitechDaily