Scandinavian Journal of Gastroenterology · 2018 · 18 citations · 16 references
Life SciencesBiochemistryOncologyGlycobiologyMolecular OncologyProteomicsCancer ProteomicsGlycan AnalysisGlycoproteomicsPancreatic CancerProtein GlycosylationTumor MarkersAberrant Glycosylation In CancerCancer Antigen 19-9Cancer DiagnosticsGlycoprotein Biomarker DiscoveryGlycoproteomic BiomarkersGlycosylation MappingSerum BiomarkersSerum Glycoproteomics
OBJECTIVE: Glycoproteomics is an emerging subfield of proteomics. Tumor-specific variations in protein glycosylation might be potential targets for the development of new cancer diagnostics. Here, we performed high-throughput screening and targeted verification of glycome alterations in serum samples from patients with pancreatic cancer and the precancerous lesion intraductal papillary mucinous neoplasm (IPMN). MATERIAL AND METHODS: The glycosylation profile of 1000 proteins was mapped in a discovery cohort comprising serum samples from 16 individuals, including 8 patients with pancreatic cancer and 8 healthy controls. The top 10 glycoprotein biomarker candidates with the highest signal intensity difference in glycosylation levels were evaluated in a cohort consisting of 109 serum samples, including 49 patients with resectable pancreatic cancer, 13 patients with resectable noninvasive IPMN and 47 healthy controls, using a targeted assay. RESULTS: Multivariable analysis defined sets of panels comprising CA19-9 and distinctively glycosylated proteins for discrimination between pancreatic cancer, IPMN and healthy controls. A panel including CA 19-9, IL.17E, B7.1 and DR6 gave an AUC of 0.988 at 100% sensitivity at 90% specificity for the discrimination of stage 1 pancreatic cancer and healthy controls. B7.1 was found to be a valuable biomarker for differentiating between IPMN and healthy controls, with better performance alone than CA 19-9. CONCLUSIONS: Measurement of protein glycosylation profiles in serum may aid in the early detection of pancreatic cancer and precursor lesions.
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Erik von Elm, Douglas G. Altman, Matthias Egger et al. · PLoS Medicine · 2007 · 21.6K citations · Full text
Public Health, Public Health Practice, Epidemiologic Methods +10
Erik von Elm, Douglas G. Altman, Matthias Egger et al. · Journal of Clinical Epidemiology · 2008 · 16.4K citations · Full text
Public Health, Public Health Practice, Epidemiologic Methods +10
pROC: an open-source package for R and S+ to analyze and compare ROC curves
Xavier Robin, Natacha Turck, Alexandre Hainard et al. · BMC Bioinformatics · 2011 · 14K citations · Full text
John P. Neoptolemos, Daniel H. Palmer, Paula Ghaneh et al. · The Lancet · 2017 · 1.9K citations · Full text
Medicine, Oncology, Pharmacotherapy +17