• Molecular & Cellular Toxicology
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• 제5권4호
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• pp.335-345
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• 2009

A major source of paeoniflorin (PF) which was from the Paeonia lactiflora root, has been used as a herbal medicine in East Asia for its antiallergic, antiinflammatory, and immunoregulatory effects. However, only few details are known about the mechanism of apoptosis induced by this compound. The present study was undertaken to further elucidate the molecular mechanism of apoptosis and the changes of gene expression elicited by PF using DNA microarrays and computational gene-expression analysis tools in human leukemia U937 cells. A comparative global transcription analysis between treatment with PF and anisomycin (AM) that induces apoptosis in U937 cells revealed that c-Jun-$NH_2$-kinase (JNK) pathway related genes were less expressed in PF-treated cells. Elucidation of the mechanisms by which PF conducts its anti-cancer activities through comparative analysis of the gene expression is necessary to provide a solid foundation for its use as a promising agent in prevention and treatment strategies.

• Molecules and Cells
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• 제38권6호
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• pp.548-561
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• 2015

By combining conventional single cell analysis with flow cytometry and public database searches with bioinformatics tools, we extended the expression profiling of thymic stromal cotransporter (TSCOT), Slc46A2/Ly110, that was shown to be expressed in bipotent precursor and cortical thymic epithelial cells. Genome scale analysis verified TSCOT expression in thymic tissue- and cell type- specific fashion and is also expressed in some other epithelial tissues including skin and lung. Coexpression profiling with genes, Foxn1 and Hoxa3, revealed the role of TSCOT during the organogenesis. TSCOT expression was detected in all thymic epithelial cells (TECs), but not in the $CD31^+$endothelial cell lineage in fetal thymus. In addition, ABC transporter-dependent side population and Sca-$1^+$ fetal TEC populations both contain TSCOT-expressing cells, indicating TEC stem cells express TSCOT. TSCOT expression was identified as early as in differentiating embryonic stem cells. TSCOT expression is not under the control of Foxn1 since TSCOT is present in the thymic rudiment of nude mice. By searching variations in the expression levels, TSCOT is positively associated with Grhl3 and Irf6. Cytokines such as IL1b, IL22 and IL24 are the potential regulators of the TSCOT expression. Surprisingly, we found TSCOT expression in the lung is diminished in lung cancers, suggesting TSCOT may be involved in the suppression of lung tumor development. Based on these results, a model for TEC differentiation from the stem cells was proposed in context of multiple epithelial organ formation.

• Genomics & Informatics
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• 제5권2호
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• pp.83-87
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• 2007

The analysis of DNA microarray data is a rapidly evolving area of bioinformatics, and various types of microarray are emerging as some of the most exciting technologies for use in biological and clinical research. In recent years, microarray technology has been utilized in various applications such as the profiling of mRNAs, assessment of DNA copy number, genotyping, and detection of methylated sequences. However, the analysis of these heterogeneous microarray platform experiments does not need to be performed separately. Rather, these platforms can be co-analyzed in combination, for cross-validation. There are a number of separate laboratory information management systems (LIMS) that individually address some of the needs for each platform. However, to our knowledge there are no unified LIMS systems capable of organizing all of the information regarding multi-platform microarray experiments, while additionally integrating this information with tools to perform the analysis. In order to address these requirements, we developed a web-based LIMS system that provides an integrated framework for storing and analyzing microarray information generated by the various platforms. This system enables an easy integration of modules that transform, analyze and/or visualize multi-platform microarray data.

• Genomics & Informatics
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• 제15권1호
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• pp.51-53
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• 2017

High-throughput transcriptome sequencing, also known as RNA sequencing (RNA-Seq), is a standard technology for measuring gene expression with unprecedented accuracy. Numerous bioconductor packages have been developed for the statistical analysis of RNA-Seq data. However, these tools focus on specific aspects of the data analysis pipeline, and are difficult to appropriately integrate with one another due to their disparate data structures and processing methods. They also lack visualization methods to confirm the integrity of the data and the process. In this paper, we propose an R-based RNA-Seq analysis pipeline called TRAPR, an integrated tool that facilitates the statistical analysis and visualization of RNA-Seq expression data. TRAPR provides various functions for data management, the filtering of low-quality data, normalization, transformation, statistical analysis, data visualization, and result visualization that allow researchers to build customized analysis pipelines.

• Bioinformatics and Biosystems
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• 제1권1호
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• pp.28-37
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• 2006

Recent studies in molecular biology and proteomics have identified a significant number of novel diagnostic, prognostic, and therapeutic disease markers. However, validation of these markers in clinical specimens with traditional histopathological techniques involves low throughput and is time consuming and labor intensive. Tissue microarrays (TMAs) offer a means of combining tens to hundreds of specimens of tissue onto a single slide for simultaneous analysis. This capability is particularly pertinent in the field of cancer for target verification of data obtained from cDNA micro arrays and protein expression profiling of tissues, as well as in epidemiology-based investigations using histochemical/immunohistochemical staining or in situ hybridization. In combination with automated image analysis, TMA technology can be used in the global cellular network analysis of tissues. In particular, this potential has generated much excitement in cardiovascular disease research. The following review discusses recent advances in the construction and application of TMAs and the opportunity for developing novel, highly sensitive diagnostic tools for the early detection of cardiovascular disease.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.113-113
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• 2017

Downy mildew (DM), caused by several species in the Peronosclerospora and Scleropthora genera, is a major maize (Zea mays L.) disease in tropical or subtropical regions. DM is an obligate parasite species in the higher plants and spreads by oospores, wind, and mycelium in seed surface, soil, and living hosts. Owing to its geographical distribution and destructive yield reduction, DM is one of the most severe maize diseases among the maize pathogens. Positional cloning in combination with phenotyping is a general approach to identify disease resistant gene candidates in plants; however, it requires several time-consuming steps including population or fine mapping. Therefore, in the present study, we suggest a new combination strategy to improve the identification of disease resistant gene candidates. Downy mildew (DM) resistant maize was selected from five cultivars using the spreader row technique. Positional cloning and bioinformatics tools identified the DM resistant QTL marker (bnlg1702) and 47 protein coding genes annotations. Eventually, 5 DM resistant gene candidates, including bZIP34, Bak1, and Ppr, were identified by quantitative RT-PCR without fine mapping of the bnlg1702 locus. Specifically, we provided DM resistant gene candidates with our new strategy, including field selection by the spreader row technique without population preparation, the DM resistance region identification by positional cloning using bioinformatics tools, and expression level profiling by quantitative RT-PCR without fine mapping. As whole genome information is available for other crops, we propose applying our novel protocol to other crops or for other diseases with suitable adjustment.

• Asian Pacific Journal of Cancer Prevention
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• 제16권12호
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• pp.4833-4837
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• 2015

Biomarkers for preclinical diagnosis of cancer are valuable tools for detection of malignant tumors at early stages in groups at risk and screening healthy people, as well as monitoring disease recurrence after treatment of cancer. However the complexity of the body's response to the pathological processes makes it virtually impossible to evaluate this response to the development of the disease using a single biomarker that is present in the serum at low concentrations. An alternative approach to standard biomarker analysis is called immunosignature. Instead of going after biomarkers themselves this approach rely on the analysis of the humoral immune response to molecular changes associated with the development of pathological processes. It is known that antibodies are produced in response to proteins expressed during cancer development. Accordingly, the changes in antibody repertoire associated with tumor growth can serve as biomarkers of cancer. Immunosignature is a highly sensitive method for antibody repertoire analysis utilizing high density peptide microarrays. In the present review we discuss modern methods for antibody detection, as well as describe the principles and applications of immunosignature in research and clinical practice.

• Asian Pacific Journal of Cancer Prevention
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• 제15권2호
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• pp.837-845
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• 2014

Background: Overweight and obesity are recognized as major drivers of cancers including breast cancer. Several cytokines, including interleukin-6 (IL-6), IL-10 and lipocalin 2 (LCN2), as well as dysregulated cell cycle proteins are implicated in breast carcinogenesis. The nuclear, casein kinase and cyclin-dependent kinase substrate-1 (NUCKS-1), is a nuclear DNA-binding protein that has been implicated in several human cancers, including breast cancer. Objectives: The present study was conducted to evaluate NUCKS-1 mRNA expression in breast tissue from obese patients with and without breast cancer and lean controls. NUCKS-1 expression was correlated to cytokine profiles as prognostic and monitoring tools for breast cancer, providing a molecular basis for a causal link between obesity and risk. Materials and Methods: This study included 39 females with breast cancer (G III) that was furtherly subdivided into two subgroups according to cancer grading (G IIIa and G IIIb) and 10 control obese females (G II) in addition to 10 age-matched healthy lean controls (G I). NUCKS-1 expression was studied in breast tissue biopsies by means of real-time PCR (RT-PCR). Serum cytokine profiles were determined by immunoassay. Lipid profiles and glycemic status as well as anthropometric measures were also recorded for all participants. Results: IL-6, IL-12 and LCN2 were significantly higher in control obese and breast cancer group than their relevant lean controls (p<0.05), while NUCKS-1 mRNA expression was significantly higher in the breast cancer group compared to the other groups (p<0.05). Significant higher levels of IL-6, IL-12, and LCN2 as well as NUCKS-1 mRNA levels were reported in G IIIb than G IIIa, and positively correlated with obesity markers in all obese patients. Conclusions: Evaluation of cytokine levels as well as related gene expression may provide a new tool for understanding interactions for three axes of carcinogenesis, innate immunity, inflammation and cell cycling, and hope for new strategies of management.