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New Liquid Biopsy Method Offers Faster, Less Invasive Brain Cancer Detection In Just One Hour

Scientists have developed a new method for detecting brain cancer that is quicker and less invasive than traditional surgical biopsies.

New Liquid Biopsy Method Offers Faster, Less Invasive Brain Cancer Detection In Just One Hour

Scientists have developed a new method for detecting brain cancer that is quicker and less invasive than traditional surgical biopsies. This innovative ‘liquid biopsy’ requires just 100 microlitres of blood and can identify biomarkers linked to glioblastoma—the most common and deadly form of brain tumor—in only one hour.

The test, which is described by its researchers as having “near turn-key functionality,” is more accurate than any previously known methods for detecting glioblastoma. Researchers from the University of Notre Dame in the U.S. teamed up with Australian scientists to create this new technique. Although it is still in its early stages, this proof of concept represents a significant advancement in diagnosing brain cancer.

According to a statement from the University of Notre Dame, the average survival time for a glioblastoma patient is 12-18 months following diagnosis. At the core of this diagnostic method is a biochip that utilizes electrokinetic technology to detect biomarkers, specifically active Epidermal Growth Factor Receptors (EGFRs), which are overexpressed in cancers like glioblastoma and are found in extracellular vesicles.

“Extracellular vesicles or exosomes are unique nanoparticles secreted by cells. They are much larger—10 to 50 times bigger than a molecule—and they carry a weak charge. Our technology was specifically designed to leverage these features,” explained Hsueh-Chia Chang, Bayer Professor of Chemical and Biomolecular Engineering at Notre Dame and lead author of the study published in Communications Biology.

Also Read: New Discovery Unveils Mysterious Ring-Like Structure in Earth’s Outer Core

The researchers faced two main challenges: developing a method to differentiate between active and inactive EGFRs, and creating a diagnostic tool that is both sensitive and selective in detecting active EGFRs on extracellular vesicles from blood samples.


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