Project title: Glycomic characterization of pancreatic neuroendocrine neoplasms

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Project Description:

Dr. Gorski and team will characterize the glycomes, or the sugar molecules, of pancreatic neuroendocrine neoplasms (PNENs) to identify a new class of candidate biomarkers and therapeutic targets for PNEN patients. 

What critical NET problem will you try to solve through your research?

PNENs are characterized by substantial molecular and clinical heterogeneity which poses challenges for effective disease management. There is a need to uncover the molecular abnormalities that drive this type of cancer and to develop strategies that reliably identify high-risk patients.

Why is this important?

Patients with PNENs can vary greatly with respect to symptoms, disease progression and treatment response, but the reasons for such dramatic patient-to-patient variability are not well understood. Through the application of glycomics, this study has the potential to uncover a new class of biomarkers to help identify high-risk patients so that they can be treated with the best options for their disease. 

What will you do as part of this research project?

Dr. Gorski (molecular and cellular biology) and team (Dr. Mahal, glycomics; Dr. Schaeffer, pathology; Dr. Loree, oncology) will characterize the pattern of glycans, or sugars, in PNEN samples. They will then determine if there is a glycan pattern associated with high-risk features that could be used to help identify high-risk patients early. The glycan patterns from PNENs will also be used to help identify potential glycan-related alterations that may contribute to disease progression. 

How might your research improve the diagnosis and/or treatment of NETs? 

Our research has the potential to improve PNEN patient outcomes by leveraging glycomics technology to identify a new class of markers to help identify patients in need of early intervention. Our work will include the characterization of molecular tools that could be relatively easily incorporated into existing clinical practice.

What is your next step?

If we identify candidate glycan-related biomarkers that associate with high-risk PNEN patients in our cohort, we will collaborate with other groups to validate these markers in additional patient cohorts for subsequent prospective studies. Glycan-related alterations that contribute to disease progression will be evaluated for therapeutic target potential. 

Outcomes:

Pancreatic neuroendocrine neoplasms (PNENs) are an uncommon type of pancreatic cancer. Patients with PNENs can vary greatly with respect to symptoms, disease progression and treatment response. At the molecular level, PNENs are also characterized by substantial variability. In many cases, the changes responsible for the disease are unknown. Together, this variability poses challenges for effective disease management. There is currently a need to uncover the molecular abnormalities that drive this type of cancer, and to develop strategies that reliably identify high-risk patients so that they can be treated with the best options for their disease. The overarching goal of this project was to apply a recently developed technology to discover a new class of markers that will help identify high-risk PNEN patients and candidate disease drivers. The technology involves the large-scale characterization of sugar modifications in PNEN cells. Previous studies in other cancer types have shown that distinct patterns of sugars are associated with high-risk disease features such as metastasis and treatment resistance but have not been well studied in PNENs. We identified and processed PNEN tissue samples from 89 patients, normal tissue samples from 10 controls, and cells from 8 different human-derived PNEN cell lines. The processed samples were evaluated using a large array of specific proteins that bind to different sugars present in the samples. We found that the PNEN samples have a distinct pattern of sugars compared to the normal tissue samples. Two classes of sugar-binding proteins had significantly lower binding, and one sugar-binding protein had significantly higher binding, in PNENs relative to the normal tissues. Across the PNEN samples, there were two subgroups with differences mainly due to a particular type of sugar modification called sialylation. Analysis of gene expression data further supports sialylation differences between PNEN samples and normal samples. We are further investigating these differences with respect to protein expression, survival outcomes and functional implications. Overall, our studies have the potential to improve PNEN patient outcomes by leveraging a recently developed technology to identify a new class of markers and candidate therapeutic targets.

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