• BMB Reports
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• v.41 no.9
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• pp.626-634
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• 2008

Novel cancer biomarkers are required to achieve early diagnosis and optimized therapy for individual patients. Cancer is a disease of the genome, and tumor tissues are a rich source of cancer biomarkers as they contain the functional translation of the genome, namely the proteome. Investigation of the tumor tissue proteome allows the identification of proteomic signatures corresponding to clinico-pathological parameters, and individual proteins in such signatures will be good biomarker candidates. Tumor tissues are also a rich source for plasma biomarkers, because proteins released from tumor tissues may be more cancer specific than those from non-tumor cells. Two-dimensional difference gel electrophoresis (2D-DIGE) with novel ultra high sensitive fluorescent dyes (CyDye DIGE Fluor satulation dye) enables the efficient protein expression profiling of laser-microdissected tissue samples. The combined use of laser microdissection allows accurate proteomic profiling of specific cells in tumor tissues. To develop clinical applications using the identified biomarkers, collaboration between research scientists, clinicians and diagnostic companies is essential, particularly in the early phases of the biomarker development projects. The proteomics modalities currently available have the potential to lead to the development of clinical applications, and channeling the wealth of produced information towards concrete and specific clinical purposes is urgent.

• Advances in environmental research
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• v.4 no.4
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• pp.247-262
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• 2015

The few lignin biomarker studies conducted in tropical environments are hampered by having to use references signatures established for plants and soils characteristic of the temperate zone. This study presents a lignin biomarker analysis (vanillyls (V), p-hydroxyls (P), syringyls (S), cinnamyls (C)) of the dominant plant species and soil horizons as well as an analysis of the interrelated terrigenous organic matter (TOM) dynamics between vegetation and soil of the $Tapaj{\acute{o}}s$ river region, an active colonization front in the Brazilian Amazon. We collected and analyzed samples from 17 fresh dominant plant species and 48 soil cores at three depths (0-5 cm, 20-25 cm, 50-55 cm) from primary rainforest, fallow forest, subsistence agriculture fields and pastures. Lignin signatures in tropical plants clearly distinguish from temperate ones with high ratios of Acid/aldehyde of vanillyls ((Ad/Al)v) and P/V+S. Contrary to temperate environments, similarly high ratios in tropical soils are not related to TOM degradation along with pedogenesis but to direct influence of plants growing on them. Lignin signatures of both plants and soils of primary rainforest and fallow forest clearly distinguish from those of non-forested areas, i.e., agriculture fields and pastures. Attalea speciosa Palm trees, an invasive species in all perturbed landscapes of the Amazon, exhibit lignin signatures clearly distinct from other dominant plant species. The study of lignin signatures in tropical areas thus represents a powerful tool to evaluate the impact of primary rainforest clearing on TOM dynamics in tropical areas.

• Asian-Australasian Journal of Animal Sciences
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• v.31 no.7
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• pp.1062-1071
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• 2018

The misuse of anabolic hormones or illegal drugs is a ubiquitous problem in animal husbandry and in food safety. The ban on growth promotants in food producing animals in the European Union is well controlled. However, application regimens that are difficult to detect persist, including newly designed anabolic drugs and complex hormone cocktails. Therefore identification of molecular endogenous biomarkers which are based on the physiological response after the illicit treatment has become a focus of detection methods. The analysis of the 'transcriptome' has been shown to have promise to discover the misuse of anabolic drugs, by indirect detection of their pharmacological action in organs or selected tissues. Various studies have measured gene expression changes after illegal drug or hormone application. So-called transcriptomic biomarkers were quantified at the mRNA and/or microRNA level by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) technology or by more modern 'omics' and high throughput technologies including RNA-sequencing (RNA-Seq). With the addition of advanced bioinformatical approaches such as hierarchical clustering analysis or dynamic principal components analysis, a valid 'biomarker signature' can be established to discriminate between treated and untreated individuals. It has been shown in numerous animal and cell culture studies, that identification of treated animals is possible via our transcriptional biomarker approach. The high throughput sequencing approach is also capable of discovering new biomarker candidates and, in combination with quantitative RT-qPCR, validation and confirmation of biomarkers has been possible. These results from animal production and food safety studies demonstrate that analysis of the transcriptome has high potential as a new screening method using transcriptional 'biomarker signatures' based on the physiological response triggered by illegal substances.

• BMB Reports
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• v.44 no.12
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• pp.765-771
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• 2011

Cancer treatment has been stratified by companion biomarker tests that serve to provide information on the genetic status of cancer patients and to identify patients who can be expected to respond to a given treatment. This stratification guarantees better efficiency and safety during treatment. Cancer patients, however, marginally benefit from the current companion biomarker-aided treatment regimens, presumably because companion biomarker tests are dependent solely on the mutation status of several genes status quo. In the true sense of the term, "personalized medicine", cancer patients are deemed to be identified individually by their molecular signatures, which are not necessarily confined to genetic mutations. Glycosylation is tremendously dynamic and shows alterations in cancer. Evidence is accumulating that aberrant glycosylation contributes to the development and progression of cancer, holding the promise for use of glycosylation status as a companion biomarker in cancer treatment. There are, however, several challenges derived from the lack of a reliable detection system for aberrant glycosylation, and a limited library of aberrant glycosylation. The challenges should be addressed if glycosylation status is to be used as a companion biomarker in cancer treatment and contribute to the fulfillment of personalized medicine.

• 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.45 no.12
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• pp.677-685
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• 2012

In the process of tumorigenesis, normal cells are remodeled to cancer cells and protein expression patterns are changed to those of tumor cells. A newly formed tumor microenvironment elicits the immune system and, as a result, a humoral immune response takes place. Although the tumor antigens are undetectable in sera at the early stage of tumorigenesis, the nature of an antibody amplification response to antigens makes tumor-associated autoantibodies as promising early biomarkers in cancer diagnosis. Moreover, the recent development of proteomic techniques that make neo-epitopes of tumor-associated autoantigens discovered concomitantly has opened a new area of 'immuno-proteomics', which presents tumor-associated autoantibody signatures and confers information to redefine the process of tumorigenesis. In this article, the strategies recently used to identify and validate serum autoantibodies are outlined and tumor-associated antigens suggested until now as diagnostic/prognostic biomarkers in various tumor types are reviewed. Also, the meaning of autoantibody signatures and their clinical utility in personalized medicine are discussed.

• Animal Bioscience
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• v.36 no.2_spc
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• pp.374-384
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• 2023

Skeletal muscle metabolism regulates homeostatic balance in animals. The metabolic impact persists even after farm animal skeletal muscle is converted to edible meat through postmortem rigor mortis and aging. Muscle metabolites resulting from animal growth and postmortem storage have a significant impact on meat quality, including flavor and color. Metabolomics studies of postmortem muscle aging have identified metabolisms that contain signatures inherent to muscle properties and the altered metabolites by physiological adaptation, with glycolysis as the pivotal metabolism in postmortem aging. Metabolomics has also played a role in mining relevant postmortem metabolisms and pathways, such as the citrate cycle and mitochondrial metabolism. This leads to a deeper understanding of the mechanisms underlying the generation of key compounds that are associated with meat quality. Genetic background, feeding strategy, and muscle type primarily determine skeletal muscle properties in live animals and affect post-mortem muscle metabolism. With comprehensive metabolite detection, metabolomics is also beneficial for exploring biomarker candidates that could be useful to monitor meat production and predict the quality traits. The present review focuses on advances in farm animal muscle metabolomics, especially postmortem muscle metabolism associated with genetic factors and muscle type.

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.6
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• pp.529-537
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• 2019

Lung cancer is the most common cause of cancer deaths worldwide and several molecular signatures have been developed to predict survival in lung cancer. Increasing evidence suggests that proliferation and migration to promote tumor growth are associated with dysregulated ion channel expression. In this study, by analyzing high-throughput gene expression data, we identify the differentially expressed $K^+$ channel genes in lung cancer. In total, we prioritize ten dysregulated $K^+$ channel genes (5 up-regulated and 5 down-regulated genes, which were designated as K-10) in lung tumor tissue compared with normal tissue. A risk scoring system combined with the K-10 signature accurately predicts clinical outcome in lung cancer, which is independent of standard clinical and pathological prognostic factors including patient age, lymph node involvement, tumor size, and tumor grade. We further indicate that the K-10 potentially predicts clinical outcome in breast and colon cancers. Molecular signature discovered through $K^+$ gene expression profiling may serve as a novel biomarker to assess the risk in lung cancer.

• Journal of Ecology and Environment
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• v.43 no.1
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• pp.31-42
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• 2019

Background: Han River estuary is a national wetland reserve near the Demilitarized Zone (DMZ) between South Korea and North Korea. This trans-boundary estuary area has been well preserved and shows distinctive plant communities along the salinity gradient. To elucidate energy flows and nutrient cycling in this area, we studied trophic relations between the dominant sesarmid crab, Sesarma dehaani, and food sources in three wetlands with different environments along the estuarine gradients. Results: Stable isotope signatures (${\delta}^{13}C$ and ${\delta}^{15}N$) of the crabs were significantly different among the sites and body size classes. Seasonal changes in ${\delta}^{13}C$ of small crabs were distinct from those of large individuals at all the sites. The isotopic values and fatty acid profiles of the crabs were more different among the sites in September than in May. In May, large-sized crabs utilized more plant materials compared to other dietary sources in contrast to small-sized crabs as revealed by a stable isotope mixing modeling, whereas contributions to diets of crabs were not dominated by a specific diet for different body size in September except at site 1. Based on PCA loadings, fatty acid content of $18:3{\omega}3$, known as a biomarker of plant materials, was the main factor to separate size groups of crabs in May and September. The ${\delta}^{13}C$ value of sediment had high correlation with those of small-sized crabs at site 1 and 2 when 1-month time lag was applied to the value for crabs during the surveyed period. Conclusions: Based on the stable isotope and fatty acid results, the consumption habits of S. dehaani appear to be distinguished by sites and their size. In particular, smaller size of S. dehaani appears to be more dependent on fewer food sources and is influenced more by the diet sources from the sediments in Han River estuary.

• Molecules and Cells
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• v.40 no.7
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• pp.466-475
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• 2017

Dietary supplements have exhibited myriads of positive health effects on human health conditions and with the advent of new technological advances, including in the fields of proteomics, genomics, and metabolomics, biological and pharmacological activities of dietary supplements are being evaluated for their ameliorative effects in human ailments. Recent interests in understanding and discovering the molecular targets of phytochemical-gene-protein-metabolite dynamics resulted in discovery of a few protein signature candidates that could potentially be used to assess the effects of dietary supplements on human health. Persimmon (Diospyros kaki) is a folk medicine, commonly used as dietary supplement in China, Japan, and South Korea, owing to its different beneficial health effects including anti-diabetic implications. However, neither mechanism of action nor molecular biomarkers have been discovered that could either validate or be used to evaluate effects of persimmon on human health. In present study, Mass Spectrometry (MS)-based proteomic studies were accomplished to discover proteomic molecular signatures that could be used to understand therapeutic potentials of persimmon leaf extract (PLE) in diabetes amelioration. Saliva, serum, and urine samples were analyzed and we propose that salivary proteins can be used for evaluating treatment effectiveness and in improving patient compliance. The present discovery proteomics study demonstrates that salivary proteomic profile changes were found as a result of PLE treatment in prediabetic subjects that could specifically be used as potential protein signature candidates.