Glycoscience aids in biomarker discovery

Hua, Serenus; An, Hyun Joo

doi:10.5483/bmbrep.2012.45.6.132

Cited by 34 publications

(34 citation statements)

References 88 publications

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“…More and more studies show that the alterations of glycosylation and the levels of glycosyltransferases activities derived from the malignant transformation are relevant to human malignancies [9]. Glycomic tools have been extensively used in the last decade for discovering biomarkers [10][11][12]. This research therefore aims to develop improved N-glycan biomarkers that would be useful in the diagnosis of patients at an increased risk of PC.…”

Section: Introductionmentioning

confidence: 97%

Validation of N-glycan markers that improve the performance of CA19-9 in pancreatic cancer

Zhao

Zhou

et al. 2015

Clin Exp Med

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Pancreatic cancer (PC) has a high mortality rate because it is usually diagnosed late. Glycosylation of proteins is known to change in tumor cells during the development of PC. The objectives of this study were to identify and validate the diagnostic value of novel biomarkers based on N-glycomic profiling for PC. In total, 217 individuals including subjects with PC, pancreatitis, and healthy controls were divided randomly into a training group (n = 164) and validation groups (n = 53). Serum N-glycomic profiling was analyzed by DSA-FACE. The diagnostic model was constructed based on N-glycan markers with logistic stepwise regression. The diagnostic performance of the model was assessed further in validation cohort. The level of total core fucose residues was increased significantly in PC. Two diagnostic models designated GlycoPCtest and PCmodel (combining GlycoPCtest and CA19-9) were constructed to differentiate PC from normal. The area under the receiver operating characteristic curve (AUC) of PCmodel was higher than that of CA19-9 (0.925 vs. 0.878). The diagnostic models based on N-glycans are new, valuable, noninvasive alternatives for identifying PC. The diagnostic efficacy is improved by combined GlycoPCtest and CA19-9 for the discrimination of patients with PC from healthy controls.

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Section: Introductionmentioning

confidence: 97%

Validation of N-glycan markers that improve the performance of CA19-9 in pancreatic cancer

Zhao

Zhou

et al. 2015

Clin Exp Med

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“…In contrast to tandem MS-centric methods, chromatographic glycan profiling can be performed on native glycans with minimal sample processing [19,35]. In particular, MS/MS structural elucidation as well as linkage-specific glycosidase digestions have previously shown chip-based porous graphitized carbon (PGC) nano-LC to be highly effective at separating isomeric oligosaccharides, glycans, and glycopeptides with high chromatographic resolution and retention time reproducibility [36–40]. LC provides a second dimension of separation that complements our previously-developed strategy for compositional glycan profiling by high-resolution MS. By coupling together reproducible isomer-sensitive LC with accurate mass MS, glycan isomers can be separated and rapidly identified according to both retention time and exact mass [33,34,36–38,41,42].…”

Section: Introductionmentioning

confidence: 99%

Isomer-specific chromatographic profiling yields highly sensitive and specific potential N-glycan biomarkers for epithelial ovarian cancer

Hua¹,

Williams²,

Dimapasoc³

et al. 2013

Journal of Chromatography A

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Aberrant glycosylation has been observed for decades in essentially all types of cancer, and is now well established as an indicator of carcinogenesis. Mining the glycome for biomarkers, however, requires analytical methods that can rapidly separate, identify, and quantify isomeric glycans. We have developed a rapid-throughput method for chromatographic glycan profiling using microfluidic chip-based nanoflow liquid chromatography (nano-LC)/mass spectrometry. To demonstrate the utility of this method, we analyzed and compared serum samples from epithelial ovarian cancer cases (n = 46) and healthy control individuals (n = 48). Over 250 N-linked glycan compound peaks with over 100 distinct N-linked glycan compositions were identified. Statistical testing identified 26 potential glycan biomarkers based on both compositional and structure-specific analyses. Using these results, an optimized model was created incorporating the combined abundances of seven potential glycan biomarkers. The receiver operating characteristic (ROC) curve of this optimized model had an area under the curve (AUC) of 0.96, indicating robust discrimination between cancer cases and healthy controls. Rapid-throughput chromatographic glycan profiling was found to be an effective platform for structure-specific biomarker discovery.

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“…The analysis of glycans involves the determination of both their composition and isomer structures. This requires specialized mass spectroscopy techniques, among others, that our group has developed (3,4, 6). …”

Section: Introductionmentioning

confidence: 99%

Evaluation of Glycomic Profiling as a Diagnostic Biomarker for Epithelial Ovarian Cancer

Kim

Ruhaak

Nguyen

et al. 2014

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background Prior studies suggested that glycans were differentially expressed in patients with ovarian cancer and controls. Wehypothesized that glycan-based biomarkers might serve as a diagnostic test for ovarian cancer and evaluated the ability of glycans to distinguish ovarian cancer cases from matched controls. Methods Serum samples were obtained from the tissue-banking repository of the Gynecologic Oncology Group, and included healthy female controls (n = 100), women diagnosed with low malignant potential (LMP) tumors (n = 52), and epithelial ovarian cancers (EOC) cases (n = 147). Cases and controls were matched on age at enrollment within ±5 years. Serum samples were analyzed by glycomics analysis to detect abundance differences in glycan expression levels. A two-stage procedure was carried out for biomarker discovery and validation. Candidate classifiers of glycans that separated cases from controls were developed using a training set in the discovery phase and the classification performance of the candidate classifiers was assessed using independent test samples that were not used in discovery. Results The patterns of glycans showed discriminatory power for distinguishing EOC and LMP cases from controls. Candidate glycan-based biomarkers developed on a training set (sensitivity, 86% and specificity, 95.8% for distinguishing EOC from controls through leave-one-out cross-validation) confirmed their potential use as a detection test using an independent test set (sensitivity, 70% and specificity, 86.5%). Conclusion Formal investigations of glycan biomarkers that distinguish cases and controls show great promise for an ovarian cancer diagnostic test. Further validation of a glycan-based test for detection of ovarian cancer is warranted. Impact An emerging diagnostic test based on the knowledge gained from understanding the glycobiology should lead to an assay that improves sensitivity and specificity and allows for early detection of ovarian cancer.

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Glycoscience aids in biomarker discovery

Cited by 34 publications

References 88 publications

Validation of N-glycan markers that improve the performance of CA19-9 in pancreatic cancer

Validation of N-glycan markers that improve the performance of CA19-9 in pancreatic cancer

Isomer-specific chromatographic profiling yields highly sensitive and specific potential N-glycan biomarkers for epithelial ovarian cancer

Evaluation of Glycomic Profiling as a Diagnostic Biomarker for Epithelial Ovarian Cancer

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