American Association for Cancer Research
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Supplemental Figure 1 from In Situ Analysis of N-Linked Glycans as Potential Biomarkers of Clinical Course in Human Prostate Cancer

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posted on 2023-04-03, 19:42 authored by Lindsey R. Conroy, Alexandra E. Stanback, Lyndsay E.A. Young, Harrison A. Clarke, Grant L. Austin, Jinze Liu, Derek B. Allison, Ramon C. Sun

Supplemental Figure 1. Hematoxylin & Eosin (H&E) staining of the three prostate TMAs used for this study.




University of Kentucky Markey Cancer Center



Prostate cancer is the most common cancer in men worldwide. Despite its prevalence, there is a critical knowledge gap in understanding factors driving disparities in survival among different cohorts of patients with prostate cancer. Identifying molecular features separating disparate populations is an important first step in prostate cancer research that could lead to fundamental hypotheses in prostate biology, predictive biomarker discovery, and personalized therapy. N-linked glycosylation is a cotranslational event during protein folding that modulates a myriad of cellular processes. Recently, aberrant N-linked glycosylation has been reported in prostate cancers. However, the full clinical implications of dysregulated glycosylation in prostate cancer has yet to be explored. Herein, we performed direct on-tissue analysis of N-linked glycans using matrix-assisted laser desorption ionization-mass spectrometry imaging (MALDI-MSI) from tissue microarrays of over 100 patient tumors with over 10 years of follow-up metadata. We successfully identified a panel of N-glycans that are unique between benign and prostate tumor tissue. Specifically, high-mannose as well as tri-and tetra-antennary N-glycans were more abundant in tumor tissue and increase proportionally with tumor grade. Further, we expanded our analyses to examine the N-glycan profiles of Black and Appalachian patients and have identified unique glycan signatures that correlate with recurrence in each population. Our study highlights the potential applications of MALDI-MSI for digital pathology and biomarker discovery for prostate cancer. MALDI-MSI identifies N-glycan perturbations in prostate tumors compared with benign tissue. This method can be utilized to predict prostate cancer recurrence and study prostate cancer disparities.

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