10.1021/pr700706s.s001 Yinghua Qiu Yinghua Qiu Tasneem H. Patwa Tasneem H. Patwa Li Xu Li Xu Kerby Shedden Kerby Shedden David E. Misek David E. Misek Missy Tuck Missy Tuck Gracie Jin Gracie Jin Mack T. Ruffin Mack T. Ruffin Danielle K. Turgeon Danielle K. Turgeon Sapna Synal Sapna Synal Robert Bresalier Robert Bresalier Norman Marcon Norman Marcon Dean E. Brenner Dean E. Brenner David M. Lubman David M. Lubman Plasma Glycoprotein Profiling for Colorectal Cancer Biomarker Identification by Lectin Glycoarray and Lectin Blot American Chemical Society 2008 glycoprotein glycosylation pattern colorectal cancer lectin affinity chromatography Colorectal Cancer Biomarker Identification Plasma Glycoprotein Profiling 10 CRC patients utility 6 colorectal cancer patients Lectin BlotColorectal cancer analysis plasma samples 2008-04-04 00:00:00 Journal contribution https://acs.figshare.com/articles/journal_contribution/Plasma_Glycoprotein_Profiling_for_Colorectal_Cancer_Biomarker_Identification_by_Lectin_Glycoarray_and_Lectin_Blot/2947054 Colorectal cancer (CRC) remains a major worldwide cause of cancer-related morbidity and mortality largely due to the insidious onset of the disease. The current clinical procedures utilized for disease diagnosis are invasive, unpleasant, and inconvenient; hence, the need for simple blood tests that could be used for the early detection of CRC. In this work, we have developed methods for glycoproteomics analysis to identify plasma markers with utility to assist in the detection of colorectal cancer (CRC). Following immunodepletion of the most abundant plasma proteins, the plasma N<i>-</i>linked glycoproteins were enriched using lectin affinity chromatography and subsequently further separated by nonporous silica reversed-phase (NPS-RP)-HPLC. Individual RP-HPLC fractions were printed on nitrocellulose coated slides which were then probed with lectins to determine glycan patterns in plasma samples from 9 normal, 5 adenoma, and 6 colorectal cancer patients. Statistical tools, including principal component analysis, hierarchical clustering, and <i>Z</i>-statistics analysis, were employed to identify distinctive glycosylation patterns. Patients diagnosed with colorectal cancer or adenomas were shown to have dramatically higher levels of sialylation and fucosylation as compared to normal controls. Plasma glycoproteins with aberrant glycosylation were identified by nano-LC−MS/MS, while a lectin blotting methodology was used to validate proteins with significantly altered glycosylation as a function of cancer progression. The potential markers identified in this study for diagnosis to distinguish colorectal cancer from adenoma and normal include elevated sialylation and fucosylation in complement C3, histidine-rich glycoprotein, and kininogen-1. These potential markers of colorectal cancer were subsequently validated by lectin blotting in an independent set of plasma samples obtained from 10 CRC patients, 10 patients with adenomas, and 10 normal subjects. These results demonstrate the utility of this strategy for the identification of N<i>-</i>linked glycan patterns as potential markers of CRC in human plasma, and may have the utility to distinguish different disease states.