• Genomics & Informatics
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• v.13 no.3
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• pp.86-89
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• 2015

Because there are clear molecular differences entailing different treatment effectiveness between Korean and non-Korean cancer patients, identifying distinct molecular characteristics of Korean cancers is profoundly important. Here, we report a web-based data repository, namely Korean Cancer Genome Database (KCGD), for searching gene signatures associated with Korean cancer patients. Currently, a total of 1,403 cancer genomics data were collected, processed and stored in our repository, an ever-growing database. We incorporated most widely used statistical survival analysis methods including the Cox proportional hazard model, log-rank test and Kaplan-Meier plot to provide instant significance estimation for searched molecules. As an initial repository with the aim of Korean-specific marker detection, KCGD would be a promising web application for users without bioinformatics expertise to identify significant factors associated with cancer in Korean.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.407-411
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• 2005

KUGI (Korean UniGene Information) database contains the annotation information of the cDNA sequences obtained from the disease samples prevalent in Korean. A total of about 157,000 5'-EST high throughput sequences collected from cDNA libraries of stomach, liver, and some cancer tissues or established cell lines from Korean patients were clustered to about 35,000 contigs. From each cluster a representative clone having the longest high quality sequence or the start codon was selected. We stored the sequences of the representative clones and the clustered contigs in the KUGI database together with their information analyzed by running Blast against RefSeq, human mRNA, and UniGene databases from NCBI. We provide a web-based search engine fur the KUGI database using two types of user interfaces: attribute-based search and similarity search of the sequences. For attribute-based search, we use DBMS technology while we use BLAST that supports various similarity search options. The search system allows not only multiple queries, but also various query types. The results are as follows: 1) information of clones and libraries, 2) accession keys, location on genome, gene ontology, and pathways to public databases, 3) links to external programs, and 4) sequence information of contig and 5'-end of clones. We believe that the KUGI database and search system may provide very useful information that can be used in the study for elucidating the causes of the disease that are prevalent in Korean.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2489-2493
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• 2015

Background: Loss of heterozygosity (LOH) on chromosomal regions is crucial in tumor progression and this study aimed to identify genome-wide LOH in pancreatic cancer. Materials and Methods: Single-nucleotide polymorphism (SNP) profiling data GSE32682 of human pancreatic samples snap-frozen during surgery were downloaded from Gene Expression Omnibus database. Genotype console software was used to perform data processing. Candidate genes with LOH were screened based on the genotype calls, SNP loci of LOH and dbSNP database. Gene annotation was performed to identify the functions of candidate genes using NCBI (the National Center for Biotechnology Information) database, followed by Gene Ontology, INTERPRO, PFAM and SMART annotation and UCSC Genome Browser track to the unannotated genes using DAVID (the Database for Annotation, Visualization and Integration Discovery). Results: The candidate genes with LOH identified in this study were MCU, MICU1 and OIT3 on chromosome 10. MCU was found to encode a calcium transporter and MICU1 could encode an essential regulator of mitochondrial $Ca^{2+}$ uptake. OIT3 possibly correlated with calcium binding revealed by the annotation analyses and was regulated by a large number of transcription factors including STAT, SOX9, CREB, NF-kB, PPARG and p53. Conclusions: Global genomic analysis of SNPs identified MICU1, MCU and OIT3 with LOH on chromosome 10, implying involvement of these genes in progression of pancreatic cancer.

• Molecules and Cells
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• v.24 no.2
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• pp.200-209
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• 2007

We generated gene expression data from the tissues of 50 gastric cancer patients, and applied meta-analysis and gene set analysis to this data and three other stomach cancer gene expression data sets to define the gene expression changes in gastric tumors. By meta-analysis we identified genes consistently changed in gastric carcinomas, while gene set analysis revealed consistently changed biological themes. Genes and gene sets involved in digestion, fatty acid metabolism, and ion transport were consistently down-regulated in gastric carcinomas, while those involved in cellular proliferation, cell cycle, and DNA replication were consistently up-regulated. We also found significant differences between the genes and gene sets expressed in diffuse and intestinal type gastric carcinoma. By gene set analysis of cytogenetic bands, we identified many chromosomal regions with possible gross chromosomal changes (amplifications or deletions). Similar analysis of transcription factor binding sites (TFBSs), revealed transcription factors that may have caused the observed gene expression changes in gastric carcinomas, and we confirmed the overexpression of one of these, E2F1, in many gastric carcinomas by tissue array and immunohistochemistry. We have incorporated the results of our meta- and gene set analyses into a web accessible database (http://human-genome.kribb.re.kr/stomach/).

• Genomics & Informatics
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• v.12 no.2
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• pp.50-57
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• 2014

We present a new next-generation sequencing-based method to identify somatic mutations of lung cancer. It is a comprehensive mutation profiling protocol to detect somatic mutations in 30 genes found frequently in lung adenocarcinoma. The total length of the target regions is 107 kb, and a capture assay was designed to cover 99% of it. This method exhibited about 97% mean coverage at $30{\times}$ sequencing depth and 42% average specificity when sequencing of more than 3.25 Gb was carried out for the normal sample. We discovered 513 variations from targeted exome sequencing of lung cancer cells, which is 3.9-fold higher than in the normal sample. The variations in cancer cells included previously reported somatic mutations in the COSMIC database, such as variations in TP53, KRAS, and STK11 of sample H-23 and in EGFR of sample H-1650, especially with more than $1,000{\times}$ coverage. Among the somatic mutations, up to 91% of single nucleotide polymorphisms from the two cancer samples were validated by DNA microarray-based genotyping. Our results demonstrated the feasibility of high-throughput mutation profiling with lung adenocarcinoma samples, and the profiling method can be used as a robust and effective protocol for somatic variant screening.

• Molecules and Cells
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• v.42 no.1
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• pp.8-16
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• 2019

Mutations in the ${\beta}-catenin$ gene (CTNNB1) have been implicated in the pathogenesis of some cancers. The recent development of cancer genome databases has facilitated comprehensive and focused analyses on the mutation status of cancer-related genes. We have used these databases to analyze the CTNNB1 mutations assembled from different tumor types. High incidences of CTNNB1 mutations were detected in endometrial, liver, and colorectal cancers. This finding agrees with the oncogenic role of aberrantly activated ${\beta}-catenin$ in epithelial cells. Elevated frequencies of missense mutations were found in the exon 3 of CTNNB1, which is responsible for encoding the regulatory amino acids at the N-terminal region of the protein. In the case of metastatic colorectal cancers, in-frame deletions were revealed in the region spanning exon 3. Thus, exon 3 of CTNNB1 can be considered to be a mutation hotspot in these cancers. Since the N-terminal region of the ${\beta}-catenin$ protein forms a flexible structure, many questions arise regarding the structural and functional impacts of hotspot mutations. Clinical identification of hotspot mutations could provide the mechanistic basis for an oncogenic role of mutant ${\beta}-catenin$ proteins in cancer cells. Furthermore, a systematic understanding of tumor-driving hotspot mutations could open new avenues for precision oncology.

• Genomics & Informatics
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• v.11 no.4
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• pp.239-244
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• 2013

Somatic mutation is a major cause of cancer progression and varied responses of tumors against anticancer agents. Thus, we must obtain and characterize genome-wide mutational profiles in individual cancer subtypes. The Cancer Genome Atlas database includes large amounts of sequencing and omics data generated from diverse human cancer tissues. In the present study, we integrated and analyzed the exome sequencing data from ~3,000 tissue samples and summarized the major mutant genes in each of the diverse cancer subtypes and stages. Mutations were observed in most human genes (~23,000 genes) with low frequency from an analysis of 11 major cancer subtypes. The majority of tissue samples harbored 20-80 different mutant genes, on average. Lung cancer samples showed a greater number of mutations in diverse genes than other cancer subtypes. Only a few genes were mutated with over 5% frequency in tissue samples. Interestingly, mutation frequency was generally similar between non-metastatic and metastastic samples in most cancer subtypes. Among the 12 major mutations, the TP53, USH2A, TTN, and MUC16 genes were found to be frequent in most cancer types, while BRAF, FRG1B, PBRM1, and VHL showed lineage-specific mutation patterns. The present study provides a useful resource to understand the broad spectrum of mutation frequencies in various cancer types.

• Genomics & Informatics
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• v.10 no.1
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• pp.23-32
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• 2012

There are lots of studies attempting to identify the expression changes in oral squamous cell carcinoma. Most studies include insufficient samples to apply statistical methods for detecting significant gene sets. This study combined two small microarray datasets from a public database and identified significant genes associated with the progress of oral squamous cell carcinoma. There were different expression scales between the two datasets, even though these datasets were generated under the same platforms - Affymetrix U133A gene chips. We discretized gene expressions of the two datasets by adjusting the differences between the datasets for detecting the more reliable information. From the combination of the two datasets, we detected 51 significant genes that were upregulated in oral squamous cell carcinoma. Most of them were published in previous studies as cancer-related genes. From these selected genes, significant genetic pathways associated with expression changes were identified. By combining several datasets from the public database, sufficient samples can be obtained for detecting reliable information. Most of the selected genes were known as cancer-related genes, including oral squamous cell carcinoma. Several unknown genes can be biologically evaluated in further studies.

• 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.

• 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.