Abstract
Abstract Colorectal cancer (CRC) is the second leading cause of cancer related deaths in the United States. A critical component of CRC care is post-surgical monitoring for cancer recurrence. Carcinogenicembryonic antigen (CEA) is a tumor marker for the clinical management of CRC which has the specific utility of monitoring post-operative disease recurrence. After surgery to remove cancerous tissue, the level of CEA in blood can be periodically monitored using an immunoassay. If the levels begin to rise above 6.0 ng/mL there is a high correlation with recurrence of the cancer. CEA, like many tumor markers is a glycoprotein and there is a significant body of work showing protein glycosylation is greatly affected by diseases such as cancer. We are investigating the CEA protein microheterogeneity in effort to improve its performance as a CRC biomarker. This poster presentation outlines our methods for glycoprotein characterization and includes qualitative and quantitative CEA glycoform data. CEA immuno-purified from cancerous liver was purchased from AbCam and processed without further purification. The purified protein was processed by SDS-PAGE on a 4-12% Bis-Tris NuPage gel (Invitrogen) in the MOPS buffer system. A second instance of the purified protein was deglycosylated with PNGaseF (New England Biolabs) and processed using the same SDS-PAGE conditions. The windows corresponding to the modified and unmodified proteins were excised and processed by in-gel digestion using a robot (ProGest, DigiLab) and Promega sequencing grade trypsin. The digested sample was analyzed by nano LC/MS/MS with a Waters NanoAcquity HPLC system interfaced to a ThermoFisher Orbitrap Velos Pro. Peptides were loaded on a trapping column and eluted over a 75µm analytical column at 350nL/min; both columns were packed with Jupiter Proteo resin (Phenomenex). The mass spectrometer was operated in data-dependent mode, with MS performed in the Orbitrap at 60,000 FWHM resolution and MS/MS performed in the dual linear ion traps. The fifteen most abundant ions were selected for MS/MS. Data were processed using bioinformatics tools and manually to identify and validate N-glycosylation sites and associated N-linked glycans. Glycoform quantitation was performed using High Resolution Accurate Mass (HRAM) and when necessary glycosites were confirmed using MS3 analysis. This presentation summarizes a workflow for the identification and quantification of protein glycoforms and shows the combination of immuno-purification, a targeted multiple enzyme approach and high resolution accurate mass data enables the accurate identification of N-glycosites and their glycoforms. The data from these experiments highlight the complexity of CEA glycoforms, for example a single N-linked glycosite on the peptide LQLSNGNR has over 30 associated glycoforms of varying abundance. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1267. doi:1538-7445.AM2012-1267
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