• 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.

• Genomics & Informatics
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• v.19 no.1
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• pp.4.1-4.9
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• 2021

Lip and oral cavity cancer, which can occur in any part of the mouth, is the 11th most common type of cancer worldwide. The major obstacles to patients' survival are the poor prognosis, lack of specific biomarkers, and expensive therapeutic alternatives. This study aimed to identify the main genes and pathways associated with lip and oral cavity carcinoma using network analysis and to analyze its molecular mechanism and prognostic significance further. In this study, 472 genes causing lip and oral cavity carcinoma were retrieved from the DisGeNET database. A protein-protein interaction network was developed for network analysis using the STRING database. VEGFA, IL6, MAPK3, INS, TNF, MAPK8, MMP9, CXCL8, EGF, and PTGS2 were recognized as network hub genes using the maximum clique centrality algorithm available in cytoHubba, and nine potential drug candidates (ranibizumab, siltuximab, sulindac, pomalidomide, dexrazoxane, endostatin, pamidronic acid, cetuximab, and apricoxib) for lip and oral cavity cancer were identified from the DGIdb database. Gene enrichment analysis was also performed to identify the gene ontology categorization of cellular components, biological processes, molecular functions, and biological pathways. The genes identified in this study could furnish a new understanding of the underlying molecular mechanisms of carcinogenesis and provide more reliable biomarkers for early diagnosis, prognostication, and treatment of lip and oral cavity cancer.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.9
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• pp.3735-3740
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• 2015

Context: Insulin-like growth factor peptides play important roles in regulating cell growth, cell differentiation, and apoptosis, and have been demonstrated to promote the development of colorectal cancer (CRC). Objective: To examine the association of insulin-related biomarkers including insulin-like growth factor-1 (IGF-1), insulin-like growth factor binding protein-3 (IGFBP-3) and C-peptide with CRC risk and assess their relevance in predictive models. Materials and Methods: The odds ratios of colorectal cancer for serum levels of IGF-1, IGFBP-3 and C-peptide were estimated using unconditional logistic regression models in 100 colorectal cancer cases and 100 control subjects. Areas under the receiving curve (AUC) and integrated discrimination improvement (IDI) statistics were used to assess the discriminatory potential of the models. Results: Serum levels of IGF-1 and IGFBP-3 were negatively associated with colorectal cancer risk (OR=0.07, 95%CI: 0.03-0.16, P for trend <.01, OR=0.06, 95%CI: 0.03-0.15, P for trend <.01 respectively) and serum C-peptide was positively associated with risk of colorectal cancer (OR=4.38, 95%CI: 2.13-9.06, P for trend <.01). Compared to the risk model, prediction for the risk of colorectal cancer had substantially improved when all selected biomarkers IGF-1, IGFBP-3 and inverse value of C-peptide were simultaneously included inthe reference model [P for AUC improvement was 0.02 and the combined IDI reached 0.166% (95 % CI; 0.114-0.219)]. Conclusions: The results provide evidence for an association of insulin-related biomarkers with colorectal cancer risk and point to consideration as candidate predictor markers.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.1
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• pp.26-33
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• 2019

Recently, the rapid growth of the companion animal market has led to the development of animal disease diagnosis kits. Therefore, the utility of the introduction of biomarkers for the development of animal molecular diagnostics is being reevaluated. A good biomarker should be precise and reliable, distinguish between normal and diseased states, and differentiate between different diseases. Recently reported genetic markers, tumor markers (cell free DNA, circulating tumor cells, granzyme, and skin tumors), and others (brucellosis, programmed death recovery-1, symmetric dimethylarginine, periostin, and cysteinyl leukotrien) have been developed. The biomarkers are used for risk prediction or for the screening, diagnosis, and monitoring of disease progression. The most important criteria for related biomarkers are disease specificity. Many potential biomarkers have emerged from laboratory and test studies, but they have not been validated in independent or large-scale clinical studies. Candidate biomarkers evaluate disease associations, verify the effectiveness of biomarkers for early detection and disease progression, and incorporate them into humans and animals. In the future, it will be necessary to reevaluate the utility of well-structured biomarker-based research and study the development of kits that can be used in on-site tests in accordance with the trends introduced in the diagnosis of animal diseases.

• Journal of Animal Science and Technology
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• v.60 no.6
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• pp.11.1-11.7
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• 2018

After pubertal, cohort of small antral follicles enters to gonadotrophin-sensitive development, called recruited follicles. This study was aimed to identify candidate genes in follicular cyclic recruitment via analysis of protein-protein interaction (PPI) network. Differentially expressed genes (DEGs) in ovine granulosa cells of small antral follicles between follicular and luteal phases were accumulated among gene/protein symbols of the Ensembl annotation. Following directed graphs, PTPN6 and FYN have the highest indegree and outdegree, respectively. Since, these hubs being up-regulated in ovine granulosa cells of small antral follicles during the follicular phase, it represents an accumulation of blood immune cells in follicular phase in comparison with luteal phase. By contrast, the up-regulated hubs in the luteal phase including CDK1, INSRR and TOP2A which stimulated DNA replication and proliferation of granulosa cells, they known as candidate genes of the cyclic recruitment.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.20
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• pp.8957-8961
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• 2014

Background: Promoter hypermethylation leads to altered gene functions and may result in malignant cellular transformation. Thus, identification of biomarkers for hypermethylated genes could be useful for diagnosis, prognosis, and therapeutic treatment of oral squamous cell carcinoma (OSCC). Objectives: To screen hypermethylated genes with a microarray approach and to validate selected hypermethylated genes with the methylation-specific polymerase chain reaction (MSPCR). Materials and Methods: Genome-wide analysis of normal oral mucosa and OSCC tissues was conducted using the Illumina methylation microarray. The specified differential genes were selected and hypermethylation status was further verified with an independent cohort sample of OSCC samples. Candidate genes were screened using microarray assay and run by MSPCR analysis. Results: TP73, PIK3R5, and CELSR3 demonstrated high percentages of differential hypermethylation status. Conclusions: Our microarray screening and MSPCR approaches revealed that the signature candidates of differentially hypermethylated genes may possibly become potential biomarkers which would be useful for diagnostic, prognostic and therapeutic targets of OSCC in the near future.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.4
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• pp.2297-2299
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• 2016

Background: Early detection of malignant transformation with expression biomarkers has significant potential to improve the survival rate of patients as such biomarkers enable prediction of progression and assess sensitivity to chemotherapy. The expression of interferon inducible transmembrane protein 1 (IFITM1) has been associated with early invasion events in several carcinomas, including head and neck cancers, and hence has been proposed as a novel candidate biomarker. As the incidence of oral squamous cell carcinoma (OSCC) is highest in the Indian population, we sought to investigate: 1) the expression pattern of IFITM1 in OSCC tissue samples obtained from Indian patients of Dravidian origin; and 2) the possibility of using IFITM1 expression as a potential biomarker. Materials and Methods: Total RNA extracted from thirty eight OSCC biopsy samples was subjected to semi-quantitative RT-PCR with IFITM1 and GAPDH specific primers. Results: Of the thirty eight OSCC samples that were analyzed, IFITM1 overexpression was identified in fifteen (39%). Seven expressed a low level, while the remainder expressed high level of IFITM1. Conclusions: The overexpression of IFITM1 in OSCC samples indicates that IFITM1 may be explored for the possibility of use as a high confidence diagnostic biomarker in oral cancers. To the best of our knowledge, this is the first time that IFITM1 overexpression is being reported in Indian OSCC samples.

• Biomolecules & Therapeutics
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• v.17 no.1
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• pp.1-11
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• 2009

Since the Committee for Proprietary Medicinal Products (CPMP) of the European Union issued in 1997 a "points to consider" document for the assessment of the potential for QT interval prolongation by non-cardiovascular agents to predict drug-induced torsades de pointes (TdP), the QT liability has become the critical safety issue in the development of pharmaceuticals. As TdP is usually linked to delayed cardiac repolarization, international guideline (ICH S7B) has advocated the standard repolarization assays such as in vitro IKr (hERG current) and in vivo QT interval, or in vitro APD (as a follow up) as the best biomarkers for predicting the TdP risk. However, the recent increasing evidence suggests that the currently used above biomarkers and/or assays are not fully predictive for TdP, but also does not address potential new druginduced TdP due to the selective disruption of hERG protein trafficking to the cell membrane or VT and/or VF with QT shortening. There is, therefore, an urgent need for other surrogate markers or assays that can predict the proarrhythmic potential of drug candidate. In this review, we provide an ideal pre-clinical strategy to predict the potentials of QT liability and lethal arrhythmia of the drug candidates with recent issues in this field in mind, not at the expense of discarding therapeutically innovative drugs.

• Journal of Veterinary Clinics
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• v.38 no.1
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• pp.21-26
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• 2021

Pyometra, a common disorder in intact bitches, can lead to canine sepsis. Identification of biomarkers for sources of infection in the uterus using two-dimensional electrophoresis (2-DE)-mass spectrometry (MS) analysis may enable the discovery of novel diagnostic markers of sepsis. Toward this end, surgically resected uterus samples from four bitches (three pyometra and one healthy) were randomly selected for 2-DE-MS, which identified 32 differentially expressed proteins, including seven inflammatory proteins, five non-inflammatory proteins, and 20 functionally unknown proteins. Despite the limited information on canine uterus proteomics, we suggest the potential use of differentially expressed uterus proteins as candidate biomarkers to discover targets to attenuate inflammation in pyometra. Further identification of the functionally unknown proteins is warranted.

• Tuberculosis and Respiratory Diseases
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• v.86 no.2
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• pp.94-101
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• 2023

A recent understanding of the dynamic continuous spectrum of Mycobacterium tuberculosis infection has led to the recognition of incipient tuberculosis, which refers to the latent infection state that has begun to progress to active tuberculosis. The importance of early detection of these individuals with a high-risk of progression to active tuberculosis is emphasized to efficiently implement targeted tuberculosis preventive therapy. However, the tuberculin skin test or interferon-γ release assay, which is currently used for the diagnosis of latent tuberculosis infection, does not aid in the prediction of the risk of progression to active tuberculosis. Thus, a novel test is urgently needed. Recently, simultaneous and systematic analysis of differentially expressed genes using a high-throughput platform has enabled the discovery of key genes that may serve potential biomarkers for the diagnosis or prognosis of diseases. This host transcriptional investigation has been extended to the field of tuberculosis, providing promising results. The present review focuses on recent progress and challenges in the field of blood transcriptional signatures to predict progression to active tuberculosis.