Detecting Early Forms Of Cancer By Analyzing Structure of Specific Sugar Molecules
- Date:
- July 12, 2008
- Source:
- Society for Experimental Biology
- Summary:
- Scientists have developed a system which can pinpoint potential "biomarkers" of early forms of cancer, by looking at structures of specific sugar molecules which are attached either to proteins of cancerous cells or to proteins involved in the host response. The availability of such cancer biomarkers could also allow disease progression and response to therapy to be monitored more easily and accurately than is currently possible.
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In order to provide the most effective treatments for cancer patients, it is essential to develop methods of sensitive and specific early detection of the disease. A team of scientists from the NIBRT Dublin-Oxford Glycobiology Laboratory at UCD has developed a system which aims to pinpoint potential "biomarkers" of early forms of the disease. They do this by looking at the structures of specific sugar molecules which are attached either to proteins made by cancerous cells or to proteins involved in the host response.
It is hoped that the availability of such cancer biomarkers would also allow disease progression and response to therapy to be monitored more accurately than is currently possible. Professor Pauline Rudd, who is leading the team, will be presenting some of their results on July 10th at the Society for Experimental Biology's Annual Meeting in Marseille.
It is known that cancer cells not only have different sets of proteins from normal human cells, but that their proteins have changes in the types and numbers of sugar molecules that are attached to them. Dr Rudd and her colleagues believe that being able to detect these changes holds the key to developing a new approach for diagnosing cancer.
"We have found that there are alterations in sugars attached to proteins in blood serum from all cancers we have looked at, and some of these appear to be early markers of the disease processes. What is more, we have been able to isolate several sugar-linked variants of particular proteins which are associated with different types of cancer, including prostate, pancreatic and ovarian and breast cancers," she reveals. "In the long term, we envisage that by finding more specific sugar variants, we will be able to use combinations of these as biomarkers to allow very accurate early diagnosis of particular cancers". These techniques could act alongside or even replace physical methods, such as scanning, which are less dependable for early diagnosis.
In order to detect differences between cancerous and normal cells, the scientists are developing a robotic technique to analyse the sugars. "Sugars are removed from the proteins and then broken down into very small components using enzymes. These fragments can be individually characterised leading to the formation of a 'fingerprint' for each sugar we analyse," Professor Rudd explains.
"By comparing the fingerprints of sugars from serum or individual proteins from cancer patients with those of disease-free people, we can find sugars which differ slightly between the two - these are the ones that are being tested as potential biomarkers. We are also refining a statistical analysis program which will enable more detailed examination of the data. As our method is high-throughput, we hope to be able to identify a large number of markers which can be taken forward for further testing and then clinical trials, leading to their potential use in both diagnosis and monitoring of cancer progression."
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Journal References:
- Royle et al. HPLC-based analysis of serum N-glycans on a 96-well plate platform with dedicated database software. Analytical Biochemistry, 2008; 376 (1): 1 DOI: 10.1016/j.ab.2007.12.012
- Tabares et al. Different glycan structures in prostate-specific antigen from prostate cancer sera in relation to seminal plasma PSA. Glycobiology, 2005; 16 (2): 132 DOI: 10.1093/glycob/cwj042
- Saldova et al. Ovarian Cancer is Associated with Changes in Glycosylation in Both Acute-Phase Proteins and IgG. Glycobiology, 2007; 17 (12): 1344 DOI: 10.1093/glycob/cwm100
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