Surface-Based Molecular Imprinting for Glycoprotein Recognition

One of the most common post-translational modifications of proteins is glycosylation, the process by which short sugar chains are selectively added to specific protein residues, resulting in a huge number of glycoprotein variants (glycoforms). There is now overwhelming evidence that glycosylation changes during the development and progression of various malignancies. Altered glycosylation has been implicated in cancer, immune deficiencies, neurodegenerative diseases, hereditary disorders and cardiovascular diseases. Many clinical biomarkers in cancer are glycoproteins, such as CEA in colorectal cancer, CA125 in ovarian cancer, HER2 in breast cancer, PSA in prostate cancer and fetoprotein in liver cancer. Glycoproteomics is rapidly emerging as an important technique for biomarker discovery, and glycoproteins are expected to become increasingly important to the diagnosis and management of human diseases.
Currently, monoclonal antibodies are playing a central role in enabling the detection of glycoprotein biomarkers using a variety of immunodiagnostic tests such as enzyme linked immunosorbant assays (ELISA). Nonetheless, monoclonal antibodies do have their own set of drawbacks that limit the commercialization of antibody sensing technology. They suffer from poor stability, need special handling and require a complicated, costly production procedure. More importantly, they lack specificity because they bind only to a small site on the biomarker (i.e. epitope) and are not able to discriminate, for instance, among different glycosylated proteins. The current antibody diagnostic technology has well recognized limitations regarding their accuracy and timeliness of disease diagnosis. This fellowship will focus on research into the means of developing a generic, robust, reliable and cost-effective alternative to monoclonal antibody technology. The fellowship aims to exploit concepts and tools from nanochemistry, supramolecular chemistry and molecular imprinting to provide highly innovative synthetic recognition platforms with high sensitivity and specificity for glycoproteins. Such novel type of platforms will make a profound and significant impact in the broad fields of biosensors and protein separation devices with applications in many areas such as biomedical diagnostics, pharmaceutical industry, defence and environmental monitoring. The proposed technology may open an untraveled path in the successful diagnosis, prognosis and monitoring of therapeutic treatment for major diseases such as cancer, immune deficiencies, neurodegenerative diseases, hereditary disorders and cardiovascular diseases.

It is expected that the work will have economic and societal impacts as well as benefiting the academic community. The novel synthetic recognition platforms will provide a new, exciting alternative to antibodies in biosensors, and permit high throughput manufacture for future real life applications. Apart from the impact on biosensors, protein separation systems would also benefit greatly from materials with the recognition properties of glycoproteins but superior robustness and reusability. Benefits in these areas will impact biomedical diagnostics (and thus patients), pharmaceutical industry, defence and environmental monitoring. UK industries can obtain licenses for our technologies to build more accurate and cheaper recognition platforms for glycoproteins. The proposed technology may open an untraveled path in the successful diagnosis, prognosis and monitoring of therapeutic treatment for major diseases such as cancer, immune deficiencies, neurodegenerative diseases, hereditary disorders and cardiovascular diseases. To consider just a few examples, the proposed diagnostic technology for glycoprotein biomarkers are expected to impact established companies in the UK such as Roche (healthcare partner with the NHS), GE Healthcare (global headquarters in the UK) and Johnson and Johnson (ortho clinical diagnostics manufacturing operations in Wales) and Novartis Diagnostics. The world market of diagnostic sensing based on antibodies is approximately £1 billion annually and our proposed technology will not only be highly competitive but also will provide new opportunities in the diagnosis of the diseases, i.e. diseases that so far have been impossible to diagnose at early stages, where the long term survival is the highest. Emerging companies are also expected to benefit from the new capabilities to be developed and they include, for example, Inanovate, a Birmingham company dedicated to the fabrication of nanostructured biochips and Serascience, part of the Abingdon Health group, which develops fast, accurate point of care tests to aid the diagnosis of myeloma and related conditions. This work is expected to have major societal impact. For instance, cancer is a major societal problem and the main cause of death in the UK. Furthermore, societal costs of cancer were calculated in 2008 to be £18 billion, and it is anticipated that these costs will increase with our ageing population to £25 billion by 2020. The platforms that we propose to develop will allow for earlier, faster and more accurate diagnosis of diseases such as cancer. Better diagnosis will result in more and better options for treatment and significant reductions in mortality, morbidity and societal costs. One example of the potential application of our approach will be realised, following completion of this fellowship. We aim to have developed an innovative screening tool for diagnostic and prognostic information in the setting of renal failure in multiple myeloma (MM) - a major cause of morbidity and mortality in MM cancer patients. Rapid accurate diagnosis is critical because reversal of renal impairment and recovery from dialysis dependency can occur with prompt appropriate treatment early in the course of disease. Thus, the development of the proposed screening tool has clear implications for the reduction of mortality and quality of life improvement of MM patients. Furthermore, screening, early detection and early treatment of kidney diseases will also result in significant reduction in healthcare costs. By preventing kidney damage or loss, it will avoid transplant or dialysis. The average cost of dialysis to the NHS is £30,800 per patient per year. It is estimated that the technology in this specific application has the potential to save NHS more than £20 million a year. The prevalence of MM increases with age, which means that the disease burden on the NHS will increase with our aging population. This is only an example of many great benefits of our technology.