BlotGlycoABC™, an Integrated Glycoblotting Technique for Rapid and Large Scale Clinical Glycomics

Miura, Yoshiaki; Hato, Masakatsu; Shinohara, Yasuro; Kuramoto, Hiromitsu; Furukawa, Yoshihiro; Kurogochi, Masaki; Shimaoka, Hideyuki; Tada, Mitsuhiro; Nakanishi, Koji; Ozaki, Michitaka; Todo, Satoru; Nishimura, Shin‐Ichiro

doi:10.1074/mcp.m700377-mcp200

Cited by 80 publications

(79 citation statements)

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“…This chemoselective glycan enrichment technology known as glycoblotting was developed in our laboratory to purify oligosaccharides derived from glycoproteins in an effective and quantitative manner, thus enabling serum glycan profiling by way of a simpler method. 20 Our method is also applicable to the fully automated analysis of multiple samples simultaneously. It readily combines the isolation and labeling of oligosaccharides, which can then be subjected to conventional analytical methods including MS. We had already achieved highspeed quantitative and qualitative profiling of glycan expression patterns in biological materials using this technology.…”

Section: Discussionmentioning

confidence: 99%

“…Using this quantitative N-glycomics procedure by way of glycoblotting technology, which is both highly accurate and can be conducted on a large scale, we have previously evaluated the potential of using N-glycans as markers of the prognosis and recurrence of HCC. 20 In our current study we evaluated preoperative blood samples from an HCC patient cohort from which we purified serum N-glycans using our glycoblotting method. 21,22 We performed N-glycan profiling using MS to search for factors related to prognosis and recurrence by analysis of patient outcomes in 369 consecutive HCC cases that had undergone a primary curative hepatectomy at our medical facility.…”

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Identification of novel serum biomarkers of hepatocellular carcinoma using glycomic analysis

et al. 2013

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The altered N-glycosylation of glycoproteins has been suggested to play an important role in the behavior of malignant cells. Using glycomics technology, we attempted to determine the specific and detailed N-glycan profile for hepatocellular carcinoma (HCC) and investigate the prognostic capabilities. From 1999 to 2011, 369 patients underwent primary curative hepatectomy in our facility and were followed up for a median of 60.7 months. As normal controls, 26 living Japanese related liver transplantation donors were selected not infected by hepatitis B and C virus. Their mean age was 40.0 and 15 (57.7%) were male. We used a glycoblotting method to purify N-glycans from preoperative blood samples from this cohort (10 lL serum) which were then identified and quantified using mass spectrometry (MS). Correlations between the N-glycan levels and the clinicopathologic characteristics and outcomes for these patients were evaluated. Our analysis of the relative areas of all the sugar peaks identified by MS, totaling 67 N-glycans, revealed that a proportion had higher relative areas in the HCC cases compared with the normal controls. Fourteen of these molecules had an area under the curve of greater than 0.80. Analysis of the correlation between these 14 N-glycans and surgical outcomes by univariate and multivariate analysis identified G2890 (m/z value, 2890.052) as a significant recurrence factor and G3560 (m/z value, 3560.295) as a significant prognostic factor. G2890 and G3560 were found to be strongly correlated with tumor number, size, and vascular invasion. Conclusion: Quantitative glycoblotting based on whole serum N-glycan profiling is an effective approach to screening for new biomarkers. The G2890 and G3560 N-glycans determined by tumor glycomics appear to be promising biomarkers for malignant behavior in HCCs. (HEPATOLOGY 2013;57:2314-2325 H epatocellular carcinoma (HCC) is a common and fatal malignancy with a worldwide occurrence.1 Liver resection has shown the highest level of control among the local treatments for HCC and is associated with a good survival rate.2,3 However, the recurrence rates for HCC are still high even when a curative hepatectomy is performed. 4 Many factors associated with the prognosis and recurrence of HCC have now been reported. Vascular invasion of the portal vein and/or hepatic vein and tumor differentiation are important factors affecting survival and recurrence in HCC cases after a hepatectomy. 5,6 However, microvascular invasion and differentiation can only be detected by pathological examination just after a hepatectomy, and cannot be diagnosed preoperatively, and thus cannot be identified preoperatively either. Hence, the serum biomarkers alpha-fetoprotein (AFP) and protein induced by vitamin K absence-II (PIVKA-II) are used as prognostic markers 7,8 and also as surrogate markers for microvascular invasion and tumor differentiation.9,10 AFP is associated with grade differentiation, 11 whereas PIVKA-II is related to vascularAbbreviations: AFP, alpha-fetoprotein; AFP-L3, lens cul...

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Section: Discussionmentioning

confidence: 99%

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Identification of novel serum biomarkers of hepatocellular carcinoma using glycomic analysis

et al. 2013

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“…2, NSTLCDLCIGPLK ϩNeuGc 2 Gal 2 -GlcNAc 2 Man 3 GlcNAc 2 ) found in the case of serotransferrin, it seems that quantitative fucosylation at this N-glycosylation site occurs specifically in the diabetic model male. This finding suggests that altered N-glycosylation in the relatively abundant serum proteins may yield distinct differences between patients and healthy controls (47,48). DISCUSSION We describe a promising method for quantitative glycoproteomics by combining the reverse glycoblotting method and MRM-based MS.…”

Section: Reproducibility Of Quantitative Mrm Assays Of Mouse Serum Simentioning

confidence: 91%

Sialic Acid-focused Quantitative Mouse Serum Glycoproteomics by Multiple Reaction Monitoring Assay

Kurogochi

Matsushista

Amano

et al. 2010

Molecular & Cellular Proteomics

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Clinical proteomics focusing on the identification and validation of biomarkers and the discovery of proteins as therapeutic targets is an emerging and highly important area of proteomics. Biomarkers are measurable indicators of a specific biological state (particularly one relevant to the risk of contraction) and the presence or the stage of disease, and are thus expected to be useful for the prediction, detection, and diagnosis of disease as well as to follow the efficacy, toxicology, and side effects of drug treatment, and to provide new functional insights into biological processes.At present, proteomics methods based on mass spectrometry (MS) have emerged as the preferred strategy for discovery of diagnostic, prognostic, and therapeutic protein biomarkers. Most biomarker discovery studies use unbiased, "identified-based" approaches that rely on high performance mass spectrometers and extensive sample processing. Semiquantitative comparisons of protein relative abundance between disease and control patient samples are used to identify proteins that are differentially expressed and, thus, to populate lists of potential biomarkers. De novo proteomics discovery experiments often result in tens to hundreds of candidate biomarkers that must be subsequently verified in serum. However, despite the large numbers of putative biomarkers, only a small number of them are passed through the development and validation process into clinical practice, and their rate of introduction is declining. The first non-standard abbreviation (MS above is standard) must be footnoted the same as the abbreviation footnote, and MRM must be the first abbreviation in the list because it is the one footnoted. After that the order does not matter.Targeted proteomics using multiple reaction monitoring (MRM) 1 is emerging as a technology that complements the discovery capabilities of shotgun strategies as well as an alternative powerful novel MS-based approach to measure a series of candidate biomarkers (1-7). Therefore, MRM is expected to provide a powerful high throughput platform for biomarker validation, although clinical validation of novel biomarkers has been traditionally relying on immunoassays (8, 9). MRM exploits the unique capabilities of triple quadrupoles (QQQ) MS for quantitative analysis. In MRM, the first and the third quadrupoles act as filters to specifically select predefined m/z values corresponding to the peptide precursor ion and specific fragment ion of the peptide, whereas the second quadrupole serves as collision cell. Several such transitions (precursor/fragment ion pairs) are monitored over time, yielding a set of chromatographic traces with retention time and signal intensity for a specific transition as coordinates. These measurements have been multiplexed to provide 30 or From the

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“…A 10-µL aliquot of whole serum or a Igs fraction purified from whole serum was processed by using the glycoblotting method [8][9][10][11][12][13][14]21] and a controlled automated SweetblotTM instrument (System Instruments, Hachioji, Japan). Then, the resulting BOA-labeled glycans were detected by MALDI-TOF MS (Ultraflex 3 TOF/TOF mass spectrometer; Bruker Daltonics, Bremen, Germany) (Figure 8).…”

Section: Glycoblotting Methods and Mass Spectrometrymentioning

confidence: 99%

Serum aberrant N-glycan profile as a marker associated with early antibody-mediated rejection in patients receiving a living donor kidney transplant

Noro¹,

Yoneyama²,

Hatakeyama³

et al. 2018

European Urology Supplements

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BlotGlycoABC™, an Integrated Glycoblotting Technique for Rapid and Large Scale Clinical Glycomics

Cited by 80 publications

References 35 publications

Identification of novel serum biomarkers of hepatocellular carcinoma using glycomic analysis

Identification of novel serum biomarkers of hepatocellular carcinoma using glycomic analysis

Sialic Acid-focused Quantitative Mouse Serum Glycoproteomics by Multiple Reaction Monitoring Assay

Serum aberrant N-glycan profile as a marker associated with early antibody-mediated rejection in patients receiving a living donor kidney transplant

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