• BMB Reports
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• v.45 no.6
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• pp.323-330
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• 2012

The glycome consists of all glycans (or carbohydrates) within a biological system, and modulates a wide range of important biological activities, from protein folding to cellular communications. The mining of the glycome for disease markers represents a new paradigm for biomarker discovery; however, this effort is severely complicated by the vast complexity and structural diversity of glycans. This review summarizes recent developments in analytical technology and methodology as applied to the fields of glycomics and glycoproteomics. Mass spectrometric strategies for glycan compositional profiling are described, as are potential refinements which allow structure-specific profiling. Analytical methods that can discern protein glycosylation at a specific site of modification are also discussed in detail. Biomarker discovery applications are shown at each level of analysis, highlighting the key role that glycoscience can play in helping scientists understand disease biology.

• Genomics & Informatics
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• v.14 no.1
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• pp.2-11
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• 2016

The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome data from tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis of global proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressed proteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicators of disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellular pathways can provide better indications of disease states than individual molecules and also network analysis of the DEPs enables effective identification of cellular pathways altered in disease conditions and key molecules representing the altered cellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways and representative molecules of such pathways have been developed. In this review, we summarize analytical platforms for network-based protein biomarker discovery and key components in the platforms.

• BMB Reports
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• v.41 no.9
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• pp.615-625
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• 2008

Over a last decade, intense interest has been focused on biomarker discovery and their clinical uses. This interest is accelerated by the completion of human genome project and the progress of techniques in proteomics. Especially, cancer biomarker discovery is eminent in this field due to its anticipated critical role in early diagnosis, therapy guidance, and prognosis monitoring of cancers. Among cancers, lung cancer, one of the top three major cancers, is the one showing the highest mortality because of failure in early diagnosis. Numerous potential DNA biomarkers such as hypermethylations of the promoters and mutations in K-ras, p53, and protein biomarkers; carcinoembryonic antigen (CEA), CYFRA21-1, plasma kallikrein B1 (KLKB1), Neuron-specific enolase, etc. have been discovered as lung cancer biomarkers. Despite extensive studies thus far, few are turned out to be useful in clinic. Even those used in clinic do not show enough sensitivity, specificity and reproducibility for general use. This review describes what the cancer biomarkers are for, various types of lung cancer biomarkers discovered at present and predicted future advance in lung cancer biomarker discovery with proteomics technology.

• Proceedings of the Korean Society of Toxicology Conference
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• 2006.05a
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• pp.45-46
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• 2006

• Proceedings of the Korean Society of Toxicology Conference
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• 2006.05a
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• pp.47-53
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• 2006

• Proceedings of the Korean Society of Toxicology Conference
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• 2005.05a
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• pp.196-196
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• 2005

• Journal of Digestive Cancer Research
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• v.3 no.1
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• pp.11-16
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• 2015

The discovery of HER2, a biomarker in advanced gastric cancer, and successful clinical trial using trastuzumab that targets this biomarker signaled a revolutionary turning point in treatment of metastatic gastric cancer. Many studies about targeted agents for gastric cancer have been attempted. Among them, ramicirumab, a monoclonal antibody that targets vascular endothelial growth factor receptor-2 (VEGFR-2), and apatinib, a tyrosine kinase inhibitor (TKI) that targets VEGFR2, have shown to improve the survival rates in advanced gastric cancer patients, for whom previous therapies had failed; hence, they are expected to be accepted as one of the standard therapies for advanced gastric cancer.

• Journal of Microbiology and Biotechnology
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• v.22 no.5
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• pp.654-658
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• 2012

Osteoarthritis (OA) is the most common rheumatic pathology. One of the major objectives of OA research is the development of early diagnostic strategies such as those using proteomic technology. Synovial fluid (SF) in OA patients is a potential source of biomarkers for OA. The efficient and reliable preparation of SF proteomes is a critical step towards biomarker discovery. In this study, we have optimized a pretreatment method for twodimensional gel electrophoresis (2DE) separation of the SF proteome, by enriching low-abundance proteins and simultaneously removing hyaluronic acid, albumin, and IgG. SF samples pretreated using this optimized method were then evaluated by 1DE and 2DE separation followed by immunodetection of cartilage oligomeric matrix protein (COMP), a known OA biomarker, and by the identification of 3 proteins (apolipoprotein, haptoglobin precursor, and fibrinogen D fragment) that are related to joint diseases.

• Mass Spectrometry Letters
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• v.1 no.1
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• pp.21-24
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• 2010

The development of clinical biomarkers involves discovery, verification, and validation. Recently, multiple reaction monitoring (MRM) coupled with stable isotope dilution mass spectrometry (IDMS) has shown considerable promise for the direct quantification of proteins in clinical samples. In particular, multiple biomarkers have been tracked in a single experiment using MRM-based MS approaches combined with liquid chromatography. We report here a highly reproducible, quantitative, and dynamic MRM system for validating multi-biomarker proteins using Nanoflow HPLC-Microfluidics Chip/Triple-Quadrupole MS. In this system, transitions were acquired only during the retention window of each eluting peptide. Transitions with the highest MRM-MS intensities for the five target peptides from colon cancer biomarker candidates were automatically selected using Optimizer software. Relative to the corresponding non-dynamic system, the dynamic MRM provided significantly improved coefficients of variation in experiments with large numbers of transitions. Linear responses were obtained with concentrations ranging from fmol to pmol for five target peptides.

• Biomedical Science Letters
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• v.29 no.4
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• pp.336-343
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• 2023

Lung cancer is one of the cancers with high mortality and incidence rates worldwide. Although, various anticancer research efforts are underway to completely treat cancer, the challenge against it remains in the inability to eliminate cancer stem cells (CSCs), leading to difficulties in curing the cancer and resulting in recurrence. As a result, there is a growing interest in the discovery of new biomarkers and therapeutic molecules that can simultaneously target both cancer cells and CSCs. From this point of view, we focused on fibronectin leucine rich transmembrane protein 3 (FLRT3), one of the genes known to be present in human lung cells and the discovery from our previous cancer proteomic analysis study. This study aimed to evaluate the potential of FLRT3 as a specific therapeutic biomarker for lung cancer and Lung Cancer-derived-Stem Cells (LCSC). Also, to estimate the biological function of FLRT3 in cancer and LCSC, short hairpin RNA (shRNA) was generated and showed the ability of the decreased-cell migration and cell proliferation of lung cancer through ERK signaling pathway when FLRT3 was knock-downed. In conclusion, our study is the first to report that FLRT3 has the potential as therapeutic biomarker for the treatment of lung cancer and LCSC.