Using magnetic resonance imaging (MRI) scans to detect sugar molecule biomarkers may improve cancer detection, Medical News Today reported.
The findings may lead to more effective biopsies, which may make some biopsies unnecessary, researchers from Johns Hopkins Medicine noted.
For their new study, researchers compared MRI readings from proteins, called mucins, with and without sugars to detect signal changes. They then looked for this signal in four types of lab-grown cancer cells, where they found notably lower levels of mucin-attached sugars, compared to normal cells.
As cells become cancerous, some proteins on their outer membranes shed sugar molecules and become less slimy, Jeff Bulte, a professor of radiology and radiological science in the Institute for Cell Engineering at the Johns Hopkins University School of Medicine, explained in a news release.
Study authors believe their research is the first time scientists have found a use in imaging cellular slime. While previous studies have found that fine-tuned MRI can detect glucose, scientists must use injectable dyes to image proteins on the outside of cells that had lost sugar.
“If we tune the MRI to detect sugars attached to a particular protein, we can see the difference between normal and cancerous cells,” Bulte said.
The technique of detecting a molecule already inside the body is advantageous as it could potentially allow lead to imaging of an entire tumor.
"This often isn't possible with injected dyes because they only reach part of the tumor. Plus, the dyes are expensive,” Xiaolei Song, the lead author on the study and a research associate in Bulte's laboratory, said in the news release.
The method has only been used in lab-grown cells and mice and the next step will be to attempt to distinguish cancerous from benign tumors in live mice. More testing is needed to understand the technique’s value in human cancer diagnosis, study authors noted.
If the tests prove the method successful, researchers believe it can be used to detect early-stage cancer or monitor chemotherapy response.
