Breast cancer is the second leading cause of cancer lethality, and the most common cancer among women;12% of American women will be diagnosed with breast cancer. Unfortunately, breast cancer is notorious for its poor prognosis and lack of effective therapeutics due to its highly metastatic nature. Proteoglycans play a critical role in cell-cell, cell-matrix interaction and regulate important signaling pathways. Inded, proteoglycans and their extracellular processing enzymes are deregulated in human breast cancers relative to normal tissues. Despite this, there is a serious lack of information concerning the mechanisms whereby cancer cells become dysregulated through altering the structures of glycosaminoglycans (GAGs) on their surfaces and in extracellular matrices. While there is a wealth of archived breast tumor tissue microarrays (TMAs) available, no methods are available for determining GAG structures and abundances from these arrays. This application aims to develop new technology to catalyze progress in cancer research for better understanding of the changes to expression of GAGs that occur as a function of breast cancer grade and stage. The challenge of cancer heterogeneity is best addressed through the analysis of the minimum number of cells possible from graded and staged biopsy samples such as those available in breast tumor TMAs. We will develop new technology with the sensitivity and speed necessary for query of the molecular structures of GAGs expressed in these tissue arrays. The ability to analyze such arrays for GAG expression is beyond any technology available at present. This proposed technology development will give cancer researchers the means to determine the mechanisms whereby cancer cells alter the structures of cell surface and extracellular matrix GAGs in order to escape normal regulatory controls and progress towards metastasis. The goal of the requested R21 activity is to develop methods and demonstrate the feasibility of quantitative structural analysis of GAGs from breast tumor tissue arrays. This will be the basis of a subsequent request for phase II (R33) activity for advanced development of the technology. We will (1) develop technology with the speed and sensitivity required for analysis of GAGs from breast cancer tissue arrays;(2) conduct a set of pilot studies on GAG expression using graded human breast cancer tissue arrays. This activity will facilitate broader use of GAG glycomics in cancer research towards a better understanding of the remodeling of cancer cell surfaces and extracellular matrices necessary for dysregulated growth and metastasis. Such technology meets the mission of the NCI's goals of funding research with high potential for positive impact on understanding of GAG expression on cancer prognosis. The proposed glycomics technology development will meet the IMAT program's goal of supporting the development of transformative technologies for cancer research.
Approximately 12% of American women will be diagnosed with breast cancer. Glycosaminoglycans and their processing enzymes are up-regulated in breast cancer. Due to the lack of effective methods, however, there is a paucity of data on the structure of glycosaminoglycans expressed in breast cancer tissue. This work will dramatically improve the ability of cancer researchers to determine such glycan structures from biopsy samples to inform understanding of cancer prognosis and application of appropriate treatment modes.
|Wu, Jiandong; Wei, Juan; Hogan, John D et al. (2018) Negative Electron Transfer Dissociation Sequencing of 3-O-Sulfation-Containing Heparan Sulfate Oligosaccharides. J Am Soc Mass Spectrom 29:1262-1272|
|Klein, Joshua A; Meng, Le; Zaia, Joseph (2018) Deep Sequencing of Complex Proteoglycans: A Novel Strategy for High Coverage and Site-specific Identification of Glycosaminoglycan-linked Peptides. Mol Cell Proteomics 17:1578-1590|
|Raghunathan, Rekha; Polinski, Nicole K; Klein, Joshua A et al. (2018) Glycomic and Proteomic Changes in Aging Brain Nigrostriatal Pathway. Mol Cell Proteomics 17:1778-1787|
|Khatri, Kshitij; Klein, Joshua A; Haserick, John R et al. (2017) Microfluidic Capillary Electrophoresis-Mass Spectrometry for Analysis of Monosaccharides, Oligosaccharides, and Glycopeptides. Anal Chem 89:6645-6655|
|Khatri, Kshitij; Klein, Joshua A; Zaia, Joseph (2017) Use of an informed search space maximizes confidence of site-specific assignment of glycoprotein glycosylation. Anal Bioanal Chem 409:607-618|
|Sethi, Manveen K; Zaia, Joseph (2017) Extracellular matrix proteomics in schizophrenia and Alzheimer's disease. Anal Bioanal Chem 409:379-394|
|Hu, Han; Khatri, Kshitij; Zaia, Joseph (2017) Algorithms and design strategies towards automated glycoproteomics analysis. Mass Spectrom Rev 36:475-498|
|Zaia, Joseph; Khatri, Kshitij; Klein, Joshua et al. (2016) Complete Molecular Weight Profiling of Low-Molecular Weight Heparins Using Size Exclusion Chromatography-Ion Suppressor-High-Resolution Mass Spectrometry. Anal Chem 88:10654-10660|
|Salanti, Ali; Clausen, Thomas M; Agerbæk, Mette Ø et al. (2015) Targeting Human Cancer by a Glycosaminoglycan Binding Malaria Protein. Cancer Cell 28:500-514|
|Turiák, Lilla; Shao, Chun; Meng, Le et al. (2014) Workflow for combined proteomics and glycomics profiling from histological tissues. Anal Chem 86:9670-8|
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