New biomarkers for pancreatic cancer are urgently needed on several fronts: screening among high-risk individuals, accurate diagnosis of suspected cancer, prognosis and treatment prediction, and monitoring the progress of tumors during the course of treatment. The CA 19-9 antigen is the best current marker for pancreatic cancer, yet its use is limited owing to its lack of expression in a significant fraction of patient. The goal of this research is to develop a panel of biomarkers for pancreatic cancer that specifically identifies patients that are either high or low in CA 19-9 and that would perform well enough to impact patient care. Research has shown that the lack of CA 19-9 elevation in certain patients is due to genetic or expression alterations in the glycosylation machinery not found in CA19-9-expressing patients. In addition, we have shown that certain patients who are low in CA 19-9 produce alternative glycans that can be used to specifically identify them. Our hypotheses are 1) the CA 19-9-low and CA 19-9-high tumors are distinct biological entities that produce divergent glycan structures;and 2) the detection of the glycans specific to CA 19-9-low tumors used in combination with the detection of CA 19-9 forms a highly accurate biomarker panel. We will use powerful glycomics tools guided by new biological/biochemical information to test these hypotheses.
In Aim 1, we will use the development of new affinity reagents combined with Shotgun Glycomics to identify and characterize glycans that may specifically detect CA 19-9-low tumors.
In Aim 2, we will derive biological information from gene expression analysis to further guide the testing of glycans for differential expression.
In Aim 3, the identified affinity reagent will be used in the testing and development of biomarker panels. The completion of these aims will result in new biomarkers to improve the care of pancreatic cancer patients, the advancement of a new strategy for identifying and developing glycan-based biomarkers, and new resources for other glycobiology projects.
Pancreatic cancer patients typically have very short survival times after diagnosis. New diagnostic methods to better identify pancreatic cancer and guide treatment decisions could greatly benefit these patients. The goal of this research is to develop such biomarkers. The initial intended use of the biomarkers resulting from this project is to improve the accuracy of early-stage diagnosis among patients with suspected cancer. Success in that area would lead to the development of these or similar markers for other needs, such as screening among high-risk individuals or selecting the best therapy for patients with confirmed cancer.
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|McCarter, Calvin; Kletter, Doron; Tang, Huiyuan et al. (2013) Prediction of glycan motifs using quantitative analysis of multi-lectin binding: Motifs on MUC1 produced by cultured pancreatic cancer cells. Proteomics Clin Appl 7:632-41|
|Fallon, Brian P; Curnutte, Bryan; Maupin, Kevin A et al. (2013) The Marker State Space (MSS) method for classifying clinical samples. PLoS One 8:e65905|
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