• Molecules and Cells
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• 제41권3호
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• pp.179-187
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• 2018

Proteomic analysis of extracellular vesicles (EVs) from biological fluid is a powerful approach to discover potential biomarkers for human diseases including cancers, as EV secreted to biological fluids are originated from the affected tissue. In order to investigate significant molecules related to the pathogenesis of bladder cancer, EVs were isolated from patient urine which was analyzed by mass spectrometry based proteomics. Comparison of the EV proteome to the whole urine proteome demonstrated an increased number of protein identification in EV. Comparative MS analyses of urinary EV from control subjects and bladder cancer patients identified a total of 1,222 proteins. Statistical analyses provided 56 proteins significantly increased in bladder cancer urine, including proteins for which expression levels varied by cancer stage (P-value < 0.05). While urine represents a valuable, non-invasive specimen for biomarker discovery in urologic cancers, there is a high degree of intra- and inter-individual variability in urine samples. The enrichment of urinary EV demonstrated its capability and applicability of providing a focused identification of biologically relevant proteins in urological diseases.

• 한국응용약물학회:학술대회논문집
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• 한국응용약물학회 2007년도 Proceedings of The Convention
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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.

• Asian Pacific Journal of Cancer Prevention
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• 제15권6호
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• pp.2511-2515
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• 2014

Objective: Lung cancer is one of the malignant tumors with greatest morbidity and mortality around the world. The keys to targeted therapy are discovery of lung cancer biomarkers to facilitate improvement of survival and quality of life for the patients with lung cancer. Translationally controlled tumor protein (TCTP) is one of the most overexpressed proteins in human lung cancer cells by comparison to the normal cells, suggesting that it might be a good biomarker for lung cancer. Materials and Methods: In the present study, the targeted efficacy of dihydroartemisinin (DHA) on TCTP expression in the A549 lung cancer cell model was explored. Results and Conclusions: DHA could inhibit A549 lung cancer cell proliferation, and simultaneously up-regulate the expression of TCTP mRNA, but down-regulate its protein expression in A549 cells. In addition, it promoted TCTP protein secretion. Therefore, TCTP might be used as a potential biomarker and therapeutic target for non-small cell lung cancers.

• Toxicological Research
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• 제26권1호
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• pp.21-28
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• 2010

As the frequency and the intensity of so called Asian dust (AD) events have increased, public concerns about the adverse health effects has spiked sharply over the last two decades. Despite the recent reports on the correlation between AD events and the risk for cardiovascular and respiratory disease, the nature of the toxicity and the degree of the risk are yet largely unknown. In the present study, we investigated the effects of the dichloromethane extract of AD (AD-X) and that of urban dust (NAD-X) collected during a non-AD period on gene expression in HL-60 cells using Illumina Sentrix HumanRef-8 Expression BeadChips. Global changes in gene expression were analyzed after 24 h of incubation with 50 or 100 ${\mu}g$/ml AD-X and NAD-X. By one-way analysis of variance (p < 0.05) and Benjamini-Hochberg multiple testing correction for false discovery rate of the results, 573 and 297 genes were identified as AD-X- and NAD-X-responsive, respectively. The genes were classified into three groups by Venn diagram analysis of their expression profile, i.e., 290 AD-X-specific, 14 NAD-X-specific, and 283 overlapping genes. Quantitative realtime PCR confirmed the changes in the expression levels of the selected genes. The expression patterns of five genes, namely SORL1, RABEPK, DDIT4, AZU1, and NUDT1 differed significantly between the two groups. Following rigorous validation process, these genes may provide information in developing biomarker for AD exposure.

• Journal of Preventive Medicine and Public Health
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• 제42권6호
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• pp.349-355
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• 2009

Biomarkers are characteristic biological properties that can be detected and measured in a variety of biological matrices in the human body, including the blood and tissue, to give an indication of whether there is a threat of disease, if a disease already exists, or how such a disease may develop in an individual case. Along the continuum from exposure to clinical disease and progression, exposure, internal dose, biologically effective dose, early biological effect, altered structure and/or function, clinical disease, and disease progression can potentially be observed and quantified using biomarkers. While the traditional discovery of biomarkers has been a slow process, the advent of molecular and genomic medicine has resulted in explosive growth in the discovery of new biomarkers. In this review, issues in evaluating biomarkers will be discussed and the biomarkers of environmental exposure, early biologic effect, and susceptibility identified and validated in epidemiological studies will be summarized. The spectrum of genomic approaches currently used to identify and apply biomarkers and strategies to validate genomic biomarkers will also be discussed.

• Molecules and Cells
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• 제44권11호
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• pp.843-850
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• 2021

The rapid increase in collateral omics and phenotypic data has enabled data-driven studies for the fast discovery of cancer targets and biomarkers. Thus, it is necessary to develop convenient tools for general oncologists and cancer scientists to carry out customized data mining without computational expertise. For this purpose, we developed innovative software that enables user-driven analyses assisted by knowledge-based smart systems. Publicly available data on mutations, gene expression, patient survival, immune score, drug screening and RNAi screening were integrated from the TCGA, GDSC, CCLE, NCI, and DepMap databases. The optimal selection of samples and other filtering options were guided by the smart function of the software for data mining and visualization on Kaplan-Meier plots, box plots and scatter plots of publication quality. We implemented unique algorithms for both data mining and visualization, thus simplifying and accelerating user-driven discovery activities on large multiomics datasets. The present Q-omics software program (v0.95) is available at http://qomics.sookmyung.ac.kr.

• Nuclear Medicine and Molecular Imaging
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• 제41권4호
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• pp.299-308
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• 2007

본 연구의 목적은 의사결정트리를 생성하는 생물정보학 프로그램을 개발하고, 이를 갑상선유두암 혈청의 질량분석자료로 시험해 보는 것이다. 대상 및 방법: C4.5를 커스터마이징하여 의사결정트리 분석을 수행할 수 있는 'Protein analysis'라는 프로그램을 개발하였다 61개의 혈청시료(갑상선유두암 27, 자가면역성 갑상선염 17, 대조군 17)를 일정 기간 동안 순차적으로 냉동한 후 실온에서 일시에 해동하여 분석에 사용하였다. 모든 시료는 탈지질화 과정을 거쳐 준비한 후, 2종류의 단백질칩(CM10, IMAC3)에 각각 60개, 50개 시료를 적용하였다. 갑상선유두암의 특징적인 단백질 패턴을 찾기 위해 질량분석기를 이용하여 단백질칩을 분석했다. 'Protein analysis' 프로그램을 이용하여 단백질분포 자료로부터 의사결정트리를 작성하고, 생체표지자 후보물질을 검출하였다. CM10칩에서 발견된 생체표지자 후보물질을 무작위 표본추출 방법을 이용하여 검증하였다. 결과: 단백질분포 자료의 훈련과 검증이 가능한 의사결정트리 프로그램이 개발되었으며, 이 프로그램은 트리 구조와 노드 정보, 트리 구성 과정을 표시하는 3개의 창으로 구성되었다. CM10칩을 이용한 분석에서 총 113개의 단백질 피크 중 23개가 3그룹 간에 유의한 차이가 있었으며, IMAC3는 41개의 단백질 피크 중 8개가 3그룹 간에 유의한 차이가 있었다. 3그룹 분석에서 의사결정트리는 CM10칩과 IMAE3의 단백질분포 자료로부터 각각 60개와 50개의 시료를 높은 정확도로 분류하였으며(오차율 = 각각 3.3%, 2.0%), 각각 4개와 7개의 생체표지자 후보물질을 검출하였다. 암시료와 비암시료를 구분하는 2그룹 분석 에서, 의사결정트리는 모든 암시료를 정확히 구분하였으며(모두 오차율 = 0%), CM10칩을 이용한 분석에서는 단일 노드를 사용하고, IMAC3칩을 이용한 분석에서는 여러 개의 노드를 사용하였다. CM10칩의 단백질 분포자료를 5번의 무작위 추출에 의해 시행한 검증에서 암시료와 비암시료를 구분하는데 높은 정확도를 보였으나(정확도 = 98%, 54/55), 3그룹을 구분할 때는 중등도의 정확도를 보였다(정확도 = 65%, 36/55). 결론: 우리가 개발한 프로그램은 질량분석 자료로부터 성공적으로 의사결정트리를 생성하고, 생체표지자 후보물질을 검출할 수 있었다. 따라서 이 프로그램은 혈청 시료를 이용한 생체표지자 발굴 및 갑상선유두암의 추적관찰에 유용하게 사용될 수 있을 것이다.

• 한국자기공명학회논문지
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• 제18권1호
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• pp.10-14
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• 2014

Hsp90 is a good drug target molecule that is involved in regulating various signaling pathway in normal cell and the role of Hsp90 is highly emphasized especially in cancer cells. Thus, much efforts for discovery and development of Hsp90 inhibitor have been continued and a few Hsp90 inhibitors targeting the N-terminal ATP binding site are being tested in the clinical trials. There are no metabolic signature molecules that can be used to evaluate the effect of Hsp90 inhibition. We previously found a potential C-domain binder named PPC1 that is a synthetic small molecule. Here we report the metabolomics study to find signature metabolites upon treatment of PPC1 compound in lung cancer cell line, A549 and discuss the potentiality of metabolomic approach for evaluation of hit compounds.

• Toxicological Research
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• 제25권2호
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• pp.59-69
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• 2009

Metabolomics which deals with the biological metabolite profile produced in the body and its relation to disease state is a relatively recent research area for drug discovery and biological sciences including toxicology and pharmacology. Metabolomics, based on analytical method and multivariate analysis, has been considered a promising technology because of its advantage over other toxicogenomic and toxicoproteomic approaches. The application of metabolomics includes the development of biomarkers associated with the pathogenesis of various diseases, alternative toxicity tests, high-throughput screening (HTS), and risk assessment, allowing the simultaneous acquisition of multiple biochemical parameters in biological samples. The metabolic profile of urine, in particular, often shows changes in response to exposure to xenobiotics or disease-induced stress, because of the biological system's attempt to maintain homeostasis. In this review, we focus on the most recent advances and applications of metabolomics in toxicological research.

• Biomolecules & Therapeutics
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• 제20권3호
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• pp.268-272
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• 2012

Nephrotoxicity occurs when kidney-specific detoxification and excretion do not work properly due to the damage or destruction of kidney function by exogenous or endogenous toxicants. Exposure to drugs often results in toxicity in kidney which represents the major control system maintaining homeostasis of body and thus is especially susceptible to xenobiotics. Understanding the toxic mechanisms for nephrotoxicity provides useful information on the development of drugs with therapeutic benefits with reduced side effects. Mechanisms for drug-induced nephrotoxicity include changes in glomerular hemodynamics, tubular cell toxicity, inflammation, crystal nephropathy, rhabdomyolysis, and thrombotic microangiopathy. Biomarkers have been identified for the assessment of nephrotoxicity. The discovery and development of novel biomarkers that can diagnose kidney damage earlier and more accurately are needed for effective prevention of drug-induced nephrotoxicity. Although some of them fail to confer specificity and sensitivity, several promising candidates of biomarkers were recently proved for assessment of nephrotoxicity. In this review, we summarize mechanisms of drug-induced nephrotoxicity and present the list of drugs that cause nephrotoxicity and biomarkers that can be used for early assessment of nephrotoxicity.