Project Summary Altered glycosylation is concomitant with malignant transformation, but the functional significance with regard to cancer progression is not well understood. This gap in knowledge is largely attributable to the difficulties associated with studying cell-surface glycoproteins. Thus, it is imperative to understand how dysregulated glycosylation contributes to immune evasion, and to develop methods that allow for facile probing of glycan changes in cancer. We seek to attain these goals with an interdisciplinary approach combining glycoproteomics, biochemistry, bioinformatics, and spatial visualization of glycans. First, glycosylation contributes to important immune signaling events within the tumor microenvironment. For instance, T cell immunoglobulin and mucin-domain containing 3 (TIM3) is an emerging checkpoint inhibitor currently under investigation for cancer immunotherapy. TIM3 is a glycosylated mucin glycoprotein, with at least 10 predicted glycosites. However, very little is known regarding TIM3 glycosylation or its effects on protein function, ligand binding, and immune signaling. One ligand of TIM3, galectin-9 (Gal-9), is known to bind glycans on TIM3 resulting in downregulation of T cell activation. The particular glycan structure and/or glycosite targeted by Gal-9 is currently unknown. Thus, in Project 1, we will probe the glycoepitope key to the Gal-9/TIM3 axis by combining intact glycoproteomics and glycome engineering with biochemical and immunological assays. In Project 2, our goal is to develop methods for visualization of O-glycan spatial distribution. Currently, the premier method to spatially examine N-glycans is MALDI mass spectrometry imaging (MSI), wherein N-glycans are removed enzymatically and imaged; however, no homologous enzyme is known for O-glycans. We will overcome this issue by using a combination of proteases selective for O-glycosylation, referred to as O- glycoproteases or mucinases. Additionally, we will perform on-tissue microscale glycoproteomics, which will allow us to couple the O-glycan MSI information with the associated glycoproteins. Together, these experiments will provide spatial resolution of dysregulated O-glycans and their underlying proteins. Finally, one of the most significant challenges currently facing the glycoproteomic field is the dearth of accurate and reliable methods for data processing. In Project 3 we seek to address this disparity by first comparing currently existing software algorithms with regard to speed, accuracy, user interface, and scoring. Our long-term goal, though, is to create a novel interface that takes advantage of my laboratory’s extensive experience with manual validation, de novo sequencing, and C# programming. Our program will include methods used inr de novo sequencing while accommodating multiple types of glycans, chemical modifications, and MALDI MSI data. Ultimately, upon attaining the goals of this proposal, the methods and insights we develop will p...