Prostate cancer is one of the most common types of cancer in men and claims over 350,000 lives worldwide every year. Early and accurate detection is critical to improve patient survival. Current diagnostic procedures are either invasive and expensive or significantly lacking accuracy. The most common screening test for prostate cancer (PCa) is the Prostate-Specific Antigen (PSA) antibody based-test but it is estimated to produce 50% false positives, translating into a large number of patients being subjected to unnecessary, costly diagnostic procedures and psychological stress. At the same time it is estimated that the PSA test misses around 25% of PCa and because of this many patients will go undiagnosed until at a more advanced stage of disease, resulting in limited treatment options and poor prognosis. PSA is a glycoprotein containing 8% of sugars with a single N-oligosaccharide chain and appears in around 50 glycoforms, but from glycoproteomic studies only a few are closely associated with PCa progression.[3-8] However, this knowledge has still not been translated into clinic due to the lack of assays that can differentiate subtle differences between sugar chains. Currently, the standard test just detects the protein and so it lumps together all the different varieties of PSA, generating a high level of false positives and false negatives.
The project aims to develop and clinically validate a sugar recognition assay for detecting PCa earlier and more effectively through a simple serum test. The assay is minimally-invasive, cost-effective and suitable for rapid, easily automatable, high-throughput screening, promoting swift clinical translation.
Recently, we have developed a synthetic detection platform on a gold sensor chip to precisely distinguish between the different types of sugars attached to proteins. The modular synthetic approach, which was developed at University of Birmingham and supported by an EPSRC Fellowship and ERC consolidator grant, is under the patent number WO2015/118294 and relies on the highly efficient generation of a pure, full complex of the sugar targets with synthetic carbohydrate receptor sites (boronic acids), in which the spatial arrangement of the multiple receptors in the complex is preserved upon sensor surface incorporation. The method works by taking sugar chain targets and essentially taking a cast of it.
Herein, we propose to capitalize on this innovative, cutting-edge technology, which detects glycans in a very specific manner, by developing a high-throughput sugar-recognition immunoassay to enable early and accurate prostate cancer detection. PSA sugars related with high-risk PCa will be molecularly casted on fluorescent nanoparticles to create surface nanopockets with sugar receptors in a specific spatial arrangement to fit only high-risk PCa sugars. A microplate assay based on the PSA immune-capture for subsequent detection of high-risk PSA using glycan-imprinted fluorescent nanoparticles will be developed and evaluated for the capability to distinguish serum samples from high and low-risk PCa patients and controls from BPH, prostatitis and non-PCa patients.
In this project, we aim to demonstrate that our assay can detect high-risk PCa with high accuracy. The novel assay has the potential for wide adoption as an accurate PCa test to identify those men that would benefit from more aggressive treatment as early as possible, and at same time, avoid biopsy and unnecessary overtreatment in men whose cancer does not threaten them, leading to significant reductions in mortality, morbidity and societal costs. Furthermore, the sugar recognition-based assay has huge potential to be expanded for early detection of other diseases, not just different type of cancers, but also immune deficiencies, neurodegenerative diseases and cardiovascular disorders since all are associated with altered protein glycosylation.
A first degree (typically BSc or Masters) in Chemistry, Material Sciences, or Biology is required. Advanced synthetic and supramolecular techniques will be used to prepare nanoparticles with glycan recognition properties. In a similar manner to that of an ELISA assay, sugar-recognition immunoassay development will entail optimization of all parameters and incubation steps to achieve maximum analytical performance. Thus, experience in nanoparticle synthesis or ELISA assay development would be advantageous.
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