• Genomics & Informatics
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• v.3 no.4
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• pp.154-158
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• 2005

Germ-line mutations of the BRCA1 gene confer an increased risk for breast and ovarian cancers. BRCA1 in female cells is directly related with the maintenance of the inactive X chromosome (Xi). The effect by the loss of the BRCA1 function on the X chromosome gene expression remains unclear in cancer cells. We attempted to investigate the expression pattern of the X-linked genes by performing BRCA1 knockdown via RNA interference in the MCF7 breast cancer cell line. The transcriptional and translational levels of BRCA1 were decreased over 95% in the MCF7 cells after BRCA1 knockdown. The expression patterns of one hundred ninety X-linked genes were profiled by the X chromosome-specific cDNA arrays. A total of seven percent of the X-linked genes (14/190) were aberrantly expressed by over 2-fold in the MCF7-BRCA1 knockdown cells, which contained two up-regulated genes (2/190, 1 %) and 12 down-regulated genes (12/190, 6.3%). It is interesting that 72% of the aberrantly expressed X-linked genes were located on the Xq (10/14,) region. Our data suggests that BRCA1 may not be important to maintain X chromosome inactivation in cancer because the BRCA1 knockdown did increase the expression of the only one percent of X-linked genes in the human breast cancer cells.

• Journal of Genetic Medicine
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• v.19 no.1
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• pp.1-6
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• 2022

Radiation therapy (RT) is a very important treatment for cancer that irradiates a large amount of radiation to lead cancer cells and tissues to death. The progression of RT in the aspect of personalized medicine has greatly advanced over the past few decades in the field of technical precision responding anatomical characteristics of each patient. However, the consideration of biological heterogeneity that makes different effect in individual patients has not actually applied to clinical practice. There have been numerous discovery and validation of biomarkers that can be applied to improve the efficiency of radiotherapy, among which those related to genomic information are very promising developments. These genome-based biomarkers can be applied to identify patients who can benefit most from altering their therapeutic dose and to select the best chemotherapy improving sensitivity to radiotherapy. The genomics-based biomarkers in radiation oncology focus on mutational changes, particularly oncogenes and DNA damage response pathways. Although few have translated into clinically viable tools, there are many promising candidates in this field. In this review the prominent mutation-based biomarkers and their potential for clinical translation will be discussed.

• 대한두경부종양학회:학술대회논문집
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• 2004.11a
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• pp.210-210
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• 2004

• Bulletin of the Korean Chemical Society
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• v.31 no.12
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• pp.3800-3802
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• 2010

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.21
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• pp.9093-9099
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• 2014

A growing body of evidence suggests that the peroxisome proliferator-activated receptor-gamma ($PPAR{\gamma}$) gene may harbor targets for the chemoprevention of breast cancer. However, it is unclear whether polymorphisms in the $PPAR{\gamma}$ gene are associated with the susceptibility of breast cancer. We performed a candidate gene association study between $PPAR{\gamma}$ polymorphisms and breast cancer and a meta-analysis on the association of breast cancer with selected $PPAR{\gamma}$ variants. Six single nucleotide polymorphisms (SNPs) in the $PPAR{\gamma}$ gene were analyzed among 456 breast cancer patients and 461 controls from the National Cancer Center in Korea. Association between the polymorphisms and breast cancer risk were assessed using the Cochrane-Armitage test for trend and a multivariate logistic regression model. Two SNPs, rs3856806 and rs1801282, had been previously analyzed, thus enabling us to perform pooled analyses on their associations with breast cancer susceptibility. Our findings from the candidate gene association study showed no association between the $PPAR{\gamma}$ gene polymorphisms and breast cancer risk. A meta-analysis combining existing studies and our current study also refuted an association of the $PPAR{\gamma}$ gene with breast cancer. Our findings suggest that the $PPAR{\gamma}$ gene may not harbor variants that alter breast cancer susceptibility, although a moderate sample size might have precluded a decisive conclusion.

• 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/).

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6281-6286
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• 2013

Background: To further investigate the molecular basis of lung cancer development, we utilize a microarray to identify differentially expressed genes associated with various TNM stages of adenocarcinoma, a subtype with increasing incidence in recent years in China. Methods: A 35K oligo gene array, covering about 25,100 genes, was used to screen differentially expressed genes among 90 tumor samples of lung adenocarcinoma in various TNM stages. To verify the gene array data, three genes (Zimp7, GINS2 and NAG-1) were confirmed by real-time RT-PCR in a different set of samples from the gene array. Results: First, we obtained 640 differentially expressed genes in lung adenocarcinomas compared to the surrounding normal lung tissues. Then, from the 640 candidates we identified 10 differentially expressed genes among different TNM stages (Stage I, II and IIIA), of which Zimp7, GINS2 and NAG-1 genes were first reported to be present at a high level in lung adenocarcinoma. The results of qRT-PCR for the three genes were consistent with those from the gene array. Conclusions: We identified 10 candidate genes associated with different TNM stages in lung adenocarcinoma in the Chinese population, which should provide new insights into the molecular basis underlying the development of lung adenocarcinoma and may offer new targets for the diagnosis, therapy and prognosis prediction.

• Molecular & Cellular Toxicology
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• v.3 no.sup4
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• pp.35.4-35.4
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• 2007

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.45-52
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• 2000

Genomic approach produces massive amount of data within a short time period, New high-throughput automatic sequencers can generate over a million nucleotide sequence information overnight. A typical DNA chip experiment produces tens of thousands expression information, not to mention the tens of megabyte image files, These data must be handled automatically by computer and stored in electronic database, Thus there is a need for systematic approach of data collection, processing, and analysis. DNA sequence information is translated into amino acid sequence and is analyzed for key motif related to its biological and/or biochemical function. Functional genomics will play a significant role in identifying novel drug targets and diagnostic markers for serious diseases. As an enabling technology for functional genomics, bioinformatics is in great need worldwide, In Korea, a new functional genomics project has been recently launched and it focuses on identi☞ing genes associated with cancers prevalent in Korea, namely gastric and hepatic cancers, This involves gene discovery by high throughput sequencing of cancer cDNA libraries, gene expression profiling by DNA microarray and proteomics, and SNP profiling in Korea patient population, Our bioinformatics team will support all these activities by collecting, processing and analyzing these data.

• BMB Reports
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• v.53 no.6
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• pp.299-310
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• 2020

Chronic liver disease progresses through several stages, fatty liver, steatohepatitis, cirrhosis, and eventually, it leads to hepatocellular carcinoma (HCC) over a long period of time. Since a large proportion of patients with HCC are accompanied by cirrhosis, it is considered to be an important factor in the diagnosis of liver cancer. This is because cirrhosis leads to an irreversible harmful effect, but the early stages of chronic liver disease could be reversed to a healthy state. Therefore, the discovery of biomarkers that could identify the early stages of chronic liver disease is important to prevent serious liver damage. Biomarker discovery at liver cancer and cirrhosis has enhanced the development of sequencing technology. Next generation sequencing (NGS) is one of the representative technical innovations in the biological field in the recent decades and it is the most important thing to design for research on what type of sequencing methods are suitable and how to handle the analysis steps for data integration. In this review, we comprehensively summarized NGS techniques for identifying genome, transcriptome, DNA methylome and 3D/4D chromatin structure, and introduced framework of processing data set and integrating multi-omics data for uncovering biomarkers.