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          New research on detecting prostate cancer

          By Liu Zhihua | chinadaily.com.cn | Updated: 2015-07-10 14:41

          A new research by University of Birmingham shows how a smart chip — capable of telling even narrow differences in glycoprotein molecules — can be used to improve the accuracy with which prostate cancer is diagnosed.

          Glycoprotein molecules, proteins that are bound to one or more carbohydrate chains, perform a wide range of functions on cell surface, structural tissues and blood. Because of their important role in immune response, they are used as clinical biomarkers to detect prostate cancer and other diseases.

          The university's team of chemical engineers and chemists created a sensor chip with synthetic receptors along a 2-D surface to identify specific, targeted glycoprotein molecules that are differentiated by their modified carbohydrate chains.

          In doing so, the new method is more accurate and efficient than the current tests relying heavily on antibodies, which are expensive to produce, subject to degeneration when exposed to environmental changes (such as high temperature or UV light) and more importantly, have a high rate of false-positive readings.

          The team developed a surface with nano-cavities that fit the particular target glycoprotein to engineer the smart chip.

          When the glycoprotein is removed 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.

          "It is essentially a lock, and the only key that will fit is the specific prostate cancer glycoprotein that we're looking for. Other glycoproteins might be the right size, but they won't be able to bind to the very specific arrangement of boron groups," says Paula Mendes, a lead researcher with the program.

          The team also hopes that further investment and collaboration with commercial partners, will open the door to adapting the current technology for other diseases.

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