Sensor Technology Can Improve Accuracy of Prostate Cancer Diagnosis

A smart sensor chip that is able to pick up on subtle differences in glycoprotein molecules can improve the accuracy and efficiency of prostate cancer diagnosis.

Glycoprotein molecules, proteins that are covalently bound to one or more carbohydrate chains, perform a wide range of functions in cell surfaces, structural tissues and blood and because of their essential role in our immune response, they are useful clinical biomarkers for detecting prostate cancer and other diseases.

Chemists at the University of Birmingham (Edgbaston, UK) created a sensor chip with synthetic receptors along a two dimensional surface to identify specific, targeted glycoprotein molecules that are differentiated by their modified carbohydrate chains. To engineer the sensor chip, the team developed a smart surface with nano-cavities that fit the particular target glycoprotein.

To create the nano-cavities, the sugar part of the prostate cancer glycoprotein is reacted with a custom-designed molecule that contains a boron group at one end as the boron linkage forms a reversible bond to the sugar. The other end of this custom molecule is made to react with molecules that have been tethered to a gold surface. The glycoprotein is then bound to the surface via its sugar groups, before the rest of the surface is blocked with a third molecule. When the glycoprotein is removed by breaking the reversible boron bonds it leaves behind a perfect cast. Within that cast, there was a special area with boron-containing molecules that can recognize a specific set of sugars. Surface plasmon resonance (SPR) analyses were performed at 25 °C with the Dual Channel SPR Spectrometer (Reichert, Buffalo, NY, USA).

John S. Fossey, PhD, a senior lecturer and a coauthor of the study, said, “It's estimated that one in eight men will suffer from prostate cancer at some point in their life, so there's a clear need for more accurate diagnosis. By focusing on the sugar, we appear to have hit the ‘sweet spot’ for doing just that. Our focus now is to take this technology and develop it into something accessible to people across the world. We believe that this could be applicable to other diagnostic challenges. Lots of diseases produce specific glycoproteins, so there are a number of possible avenues to improve the accuracy of our diagnoses.” The study was published on June 17, 2015, in the journal Chemical Science.

Related Links:
University of Birmingham
Reichert