The prevalence and nature of glycan alterations on specific proteins in pancreatic cancer patients revealed using antibody-lectin sandwich arrays

使用抗体-凝集素夹心阵列揭示胰腺癌患者特定蛋白质中糖基改变的普遍性和性质

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作者:Tingting Yue, Irwin J Goldstein, Michael A Hollingsworth, Karen Kaul, Randall E Brand, Brian B Haab

Abstract

Changes to the glycan structures of proteins secreted by cancer cells are known to be functionally important and to have potential diagnostic value. However, an exploration of the population variation and prevalence of glycan alterations on specific proteins has been lacking because of limitations in conventional glycobiology methods. Here we report the use of a previously developed antibody-lectin sandwich array method to characterize both the protein and glycan levels of specific mucins and carcinoembryonic antigen-related proteins captured from the sera of pancreatic cancer patients (n = 23) and control subjects (n = 23). The MUC16 protein was frequently elevated in the cancer patients (65% of the patients) but showed no glycan alterations, whereas the MUC1 and MUC5AC proteins were less frequently elevated (30 and 35%, respectively) and showed highly prevalent (up to 65%) and distinct glycan alterations. The most frequent glycan elevations involved the Thomsen-Friedenreich antigen, fucose, and Lewis antigens. An unexpected increase in the exposure of alpha-linked mannose also was observed on MUC1 and MUC5ac, indicating possible N-glycan modifications. Because glycan alterations occurred independently from the protein levels, improved identification of the cancer samples was achieved using glycan measurements on specific proteins relative to using the core protein measurements. The most significant elevation was the cancer antigen 19-9 on MUC1, occurring in 19 of 23 (87%) of the cancer patients and one of 23 (4%) of the control subjects. This work gives insight into the prevalence and protein carriers of glycan alterations in pancreatic cancer and points to the potential of using glycan measurements on specific proteins for highly effective biomarkers.

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