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.

Public Health Relevance

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.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA168896-04
Application #
8895753
Study Section
Special Emphasis Panel (ZCA1-SRLB-4 (M1))
Program Officer
Rinaudo, Jo Ann S
Project Start
2012-08-08
Project End
2017-06-30
Budget Start
2015-07-01
Budget End
2016-06-30
Support Year
4
Fiscal Year
2015
Total Cost
$433,792
Indirect Cost
$99,284
Name
Van Andel Research Institute
Department
Type
DUNS #
129273160
City
Grand Rapids
State
MI
Country
United States
Zip Code
49503
Klamer, Zachary; Staal, Ben; Prudden, Anthony R et al. (2017) Mining High-Complexity Motifs in Glycans: A New Language To Uncover the Fine Specificities of Lectins and Glycosidases. Anal Chem 89:12342-12350
Barnett, Daniel; Liu, Ying; Partyka, Katie et al. (2017) The CA19-9 and Sialyl-TRA Antigens Define Separate Subpopulations of Pancreatic Cancer Cells. Sci Rep 7:4020
Tang, Huiyuan; Partyka, Katie; Hsueh, Peter et al. (2016) Glycans related to the CA19-9 antigen are elevated in distinct subsets of pancreatic cancers and improve diagnostic accuracy over CA19-9. Cell Mol Gastroenterol Hepatol 2:201-221.e15
Reatini, Bryan S; Ensink, Elliot; Liau, Brian et al. (2016) Characterizing Protein Glycosylation through On-Chip Glycan Modification and Probing. Anal Chem 88:11584-11592
Sinha, Jessica; Cao, Zheng; Dai, Jianliang et al. (2016) A Gastric Glycoform of MUC5AC Is a Biomarker of Mucinous Cysts of the Pancreas. PLoS One 11:e0167070
Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep et al. (2015) Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data. Anal Chem 87:9715-21
Tang, Huiyuan; Singh, Sudhir; Partyka, Katie et al. (2015) Glycan motif profiling reveals plasma sialyl-lewis x elevations in pancreatic cancers that are negative for sialyl-lewis A. Mol Cell Proteomics 14:1323-33
Tang, Huiyuan; Hsueh, Peter; Kletter, Doron et al. (2015) The detection and discovery of glycan motifs in biological samples using lectins and antibodies: new methods and opportunities. Adv Cancer Res 126:167-202
Singh, Sudhir; Pal, Kuntal; Yadav, Jessica et al. (2015) Upregulation of glycans containing 3' fucose in a subset of pancreatic cancers uncovered using fusion-tagged lectins. J Proteome Res 14:2594-605
Kletter, Doron; Curnutte, Bryan; Maupin, Kevin A et al. (2015) Exploring the specificities of glycan-binding proteins using glycan array data and the GlycoSearch software. Methods Mol Biol 1273:203-14

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