• Proceedings of the Korean Society for Bioinformatics Conference
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• 2006.02a
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• pp.83-89
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• 2006

Cellular functions are carried out by a concerted action of biochemical pathways whose components have genetic interactions. Abnormalities in the activity of the genes that constitute or modulate these pathways frequently have oncogenic implications. Therefore, identifying the upstream regulatory genes for major biochemical pathways and defining their roles in carcinogenesis can have important consequences in establishing an effective target-oriented antitumor strategy We have analyzed the gene expression profiles of human liver cancer samples using cDNA microarray chips enriched in liver and/or stomach-expressed cDNA elements, and identified groups of genes that can tell tumors from non-tumors or normal liver, or classify tumors according to clinical parameters such as tumor grade, age, and inflammation grade. We also set up a high-throughput cell-based assay system (cell chip) that can monitor the activity of major biochemical pathways through a reporter assay. Then, we applied the cell chip platform for the analysis of the HCC-associated genes discovered from transcriptome profiling, and found a number of cancer marker genes having a potential of modulating the activity of cancer-related biochemical pathways such as E2F, TCF, p53, Stat, Smad, AP-1, c-Myc, HIF and NF-kB. Some of these marker genes were previously blown to modulate these pathways, while most of the others not. Upon a fast-track phenotype analysis, a subset of the genes showed increased colony forming abilities in soft agar and altered cell morphology or adherence characteristics in the presence of purified matrix proteins. We are currently analyzing these selected marker genes in more detail for their effects on various biological Processes and for Possible clinical roles in liver cancer development.

• Journal of Ginseng Research
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• v.41 no.1
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• pp.60-68
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• 2017

Background: Various Panax ginseng cultivars exhibit a range of diversity for morphological and physiological traits. However, there are few studies on diversity of metabolic profiles and genetic background to understand the complex metabolic pathway in ginseng. Methods: To understand the complex metabolic pathway and related genes in ginseng, we tried to conduct integrated analysis of primary metabolite profiles and related gene expression using five ginseng cultivars showing different morphology. We investigated primary metabolite profiles via gas chromatography-mass spectrometry (GC-MS) and analyzed transcriptomes by Illumina sequencing using adventitious roots grown under the same conditions to elucidate the differences in metabolism underlying such genetic diversity. Results: GC-MS analysis revealed that primary metabolite profiling allowed us to classify the five cultivars into three independent groups and the grouping was also explained by eight major primary metabolites as biomarkers. We selected three cultivars (Chunpoong, Cheongsun, and Sunhyang) to represent each group and analyzed their transcriptomes. We inspected 100 unigenes involved in seven primary metabolite biosynthesis pathways and found that 21 unigenes encoding 15 enzymes were differentially expressed among the three cultivars. Integrated analysis of transcriptomes and metabolomes revealed that the ginseng cultivars differ in primary metabolites as well as in the putative genes involved in the complex process of primary metabolic pathways. Conclusion: Our data derived from this integrated analysis provide insights into the underlying complexity of genes and metabolites that co-regulate flux through these pathways in ginseng.

• BMB Reports
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• v.56 no.10
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• pp.563-568
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• 2023

DNA methylation regulates gene expression and contributes to tumorigenesis in the early stages of cancer. In colorectal cancer (CRC), CpG island methylator phenotype (CIMP) is recognized as a distinct subset that is associated with specific molecular and clinical features. In this study, we investigated the genome-wide DNA methylation patterns among patients with CRC. The methylation data of 1 unmatched normal, 142 adjacent normal, and 294 tumor samples were analyzed. We identified 40,003 differentially methylated positions with 6,933 (79.8%) hypermethylated and 16,145 (51.6%) hypomethylated probes in the genic region. Hypermethylated probes were predominantly found in promoter-like regions, CpG islands, and N shore sites; hypomethylated probes were enriched in open-sea regions. CRC tumors were categorized into three CIMP subgroups, with 90 (30.6%) in the CIMP-high (CIMP-H), 115 (39.1%) in the CIMP-low (CIMP-L), and 89 (30.3%) in the non-CIMP group. The CIMP-H group was associated with microsatellite instability-high tumors, hypermethylation of MLH1, older age, and right-sided tumors. Our results showed that genome-wide methylation analyses classified patients with CRC into three subgroups according to CIMP levels, with clinical and molecular features consistent with previous data.