• Proceedings of the Korean Society of Toxicology Conference
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• 2005.05a
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• pp.205-205
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• 2005

• Proceedings of the Korean Society of Applied Entomolohy Conference
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• 2005.05a
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• pp.188-188
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• 2005

• Biomedical Science Letters
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• v.21 no.1
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• pp.1-8
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• 2015

Alzheimer's disease is a common form of dementia occurring among the elderly population and can be identified by symptoms such as cognition impairments, memory loss and neuronal dysfunction. Alzheimer's disease was found to be caused by the deposition of $\beta$-amyloid plaques and neurofibrillary tangles. In addition, mutation in the APP (Amyloid precursor protein), Presenilin 1 (PSEN1) and Presenilin 2 (PSEN2) genes were also found to contribute to Alzheimer's disease. Since the potential conformational diagnosis of Alzheimer's disease requires histopathological tests on brain through autopsy, potential early diagnosis still remains challenging. In recent years, several researches have proposed the use of biomarkers for early diagnosis. In cerebrospinal fluid (CSF), $\beta$-amyloid(1-42), phosphorylated-tau and total tau were suggested to be effective biomarkers for Alzheimer's disease diagnosis. However, a single biomarker might not be sufficient for potential diagnosis of Alzheimer's disease. Thus, the use of RNA interference (RNAi) through microRNAs (miRNAs) has been proposed by several researchers for simultaneous analysis of several biomarkers using microarray technology. These miRNA based biomarkers can be analysed from both blood and CSF, but miRNAs from blood are advantageous over CSF as they are non-invasive and simple for collection. Moreover, the RNAi based therapeutics by siRNA (short interference RNA) or shRNA (short hairpin RNA) have also been proposed to be effective in the treatment of Alzheimer's disease. This review describes the promising application of RNAi technology in therapeutics and as a biomarker for both Alzheimer's disease diagnosis and treatment.

• Environmental Analysis Health and Toxicology
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• v.24 no.2
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• pp.107-117
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• 2009

Metal pollution of aquatic ecosystems is a problem of economic and health importance. Information regarding molecular responses to metal exposure is sorely needed in order to identify potential biomarkers. To determine the effects of heavy metals on chironomids, the full-length cDNA of alcohol dehydrogenase (ADH3) from Chironomus riparius was determined through molecular cloning and rapid amplification of cDNA ends (RACE). The expression of ADH3 was analyzed under various cadmium and copper concentrations. A comparative and phylogenetic study among different orders of insects and vertebrates was carried out through analysis of sequence databases. The complete cDNA sequence of the ADH3 gene was 1134 bp in length. The sequence of C. riparius ADH3 shows a low degree of amino acid identity (around 70%) with homologous sequences in other insects. After exposure of C. riparius to various concentrations of copper, ADH3 gene expression significantly decreased within 1 hour. The ADH3 gene expression was also suppressed in C. riparius after cadmium exposure for 24 hour. However, the effect of cadmium on ADH3 gene expression was transient in C. riparius. The results show that the suppression of ADH3 gene by copper exposure could be used as a possible biomarker in aquatic environmental monitoring and imply differential toxicity to copper and cadmium in C. riparius larvae.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2007.11a
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• pp.19-27
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• 2007

An important potential of metabolomics-based approach is the possibility to develop fingerprints of diseases or cellular responses to classes of compounds with known common biological effect. Such fingerprints have the potential to allow classification of disease states or compounds, to provide mechanistic information on cellular perturbations and pathways and to identify biomarkers specific for disease severity and drug efficacy. Metabolic profiles of biological fluids contain a vast array of endogenous metabolites. Changes in those profiles resulting from perturbations of the system can be observed using analytical techniques, such as NMR and MS. $^1H$ NMR was used to generate a molecular fingerprint of serum or urinary sample, and then pattern recognition technique was applied to identity molecular signatures associated with the specific diseases or drug efficiency. Several metabolites that differentiate disease samples from the control were thoroughly characterized by NMR spectroscopy. We investigated the metabolic changes in human normal and clinical samples using $^1H$ NMR. Spectral data were applied to targeted profiling and spectral binning method, and then multivariate statistical data analysis (MVDA) was used to examine in detail the modulation of small molecule candidate biomarkers. We show that targeted profiling produces robust models, generates accurate metabolite concentration data, and provides data that can be used to help understand metabolic differences between healthy and disease population. Such metabolic signatures could provide diagnostic markers for a disease state or biomarkers for drug response phenotypes.

• 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.

• BMB Reports
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• v.56 no.6
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• pp.341-346
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• 2023

Acute myocardial infarction (AMI) is a multifaceted syndrome influenced by the functions of various extrinsic and intrinsic pathways and pathological processes, which can be detected in circulation using biomarkers. In this study, we investigated the secretome protein profile of induced-hypertrophy cardiomyocytes to identify next-generation biomarkers for AMI diagnosis and management. Hypertrophy was successfully induced in immortalized human cardiomyocytes (T0445) by 200 nM ET-1 and 1 μM Ang II. The protein profiles of hypertrophied cardiomyocyte secretomes were analyzed by nano-liquid chromatography with tandem mass spectrometry and differentially expressed proteins that have been identified by Ingenuity Pathway Analysis. The levels of 32 proteins increased significantly (>1.4 fold), whereas 17 proteins (<0.5 fold) showed a rapid decrease in expression. Proteomic analysis showed significant upregulation of six 14-3-3 protein isoforms in hypertrophied cardiomyocytes compared to those in control cells. Multi-reaction monitoring results of human plasma samples showed that 14-3-3 protein-zeta levels were significantly elevated in patients with AMI compared to those of healthy controls. These findings elucidated the role of 14-3-3 protein-zeta in cardiac hypertrophy and cardiovascular disorders and demonstrated its potential as a novel biomarker and therapeutic strategy.

• BMB Reports
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• v.57 no.7
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• pp.324-329
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• 2024

The aim of the present study is to provide a rational background for silencing the V-set and transmembrane domain containing 2 like (VSTM2L) in consort with recognising soluble VSTM2L against cholangiocarcinoma. A therapeutic target against cholangiocarcinoma was selected using iterative patient partitioning (IPP) calculation, and it was verified by in vitro and in silico analyses. VSTM2L was selected as a potential therapeutic target against cholangiocarcinoma. Silencing the VSTM2L expression significantly attenuated the viability and survival of cholangiocarcinoma cells through blockade of the intracellular signalling pathway. In silico analysis showed that VSTM2L affected the positive regulation of cell growth in cholangiocarcinoma. Liptak's z value revealed that the expression of VSTM2L worsened the prognosis of cholangiocarcinoma patients. In addition, soluble VSTM2L was significantly detected in the whole blood of cholangiocarcinoma patients compared with that of healthy donors. Our report reveals that VSTM2L might be the potential therapeutic target and a soluble prognostic biomarker against cholangiocarcinoma.

• Korean Journal of Ecology and Environment
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• v.48 no.2
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• pp.86-94
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• 2015

Chironomous is aquatic insect belonging to order Diptera, family Chironomidae. Their larval stage can be found mainly in aquatic benthic environment, hence good model organism to study environmental toxicology assessments and consider as useful bio indicators of contamination of the aquatic environment. In this study, Chironomus Heat Shock Proteins, Cytochrome 450, Glutathione S-transferase, Serine-type endopeptidase gene expressions were compared between polluted field areas (Chironomus plumosus) and under laboratory conditions (Chironomus riparious) to investigate molecular indicators for environmental contaminant stress assessment. Heavy metal (Al, Fe, Mn, Cu, Cr, Zn, Se, Pb, As, Cd) concentrations in sediments collected from three study areas exceeded the reference values. Moreover, HSPs, CYP450 and GST gene expression except SP for C. plumosus showed higher expression than C. riparious gene expression. Similar gene expression pattern was observed in C. riparious that exposed environment waters up to 96 h when compared to C. plumosus exposed to waters that grown in lab conditions. In summary, this comparative gene expression analysis in Chironomous between field and laboratory condition gave useful information to select candidate molecular indicators in heavy metal contaminations in the environment.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.299-308
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• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.