• Molecular & Cellular Toxicology
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• 제5권1호
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• pp.32-43
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• 2009

Acetaminophen (APAP) overdose is known to cause severe hepatotoxicity mainly through the depletion of glutathione. In this study, we compared the cytotoxic effects of APAP on both a normal murine hepatic cell line, BNL CL.2, and its SV40-transformed cell line, BNL SV A.8. Gene expression profiles for APAP-treated cells were also obtained using microarray and analyzed to identify differences in genes or profiles that may explain the differences of susceptibility to APAP in these cell lines. These two cell lines exhibited different susceptibilities to APAP (0-$5,000{\mu}M$); BNL SV A.8 cells were more susceptible to APAP treatment compared to BNL CL.2 cells. A dose of $625{\mu}M$ APAP, which produced significant differences in cytotoxicity in these cell lines, was tested. Microarray analysis was performed to identify significant differentially expressed genes (DEGs) irrespective of APAP treatment. Genes up-regulated in BNL SV A.8 cells were associated with immune response, defense response, and apoptosis, while down-regulated genes were associated with catalytic activity, cell adhesion and the cytochrome P450 family. Consistent with the cytotoxicity data, no significant DEGs were found in BNL CL.2 cells after treatment with $625{\mu}M$ APAP, while cell cycle arrest and apoptosis-related genes were up-regulated in BNL SV A.8 cells. Based on the significant fold-changes in their expression, a genes were selected and their expressions were confirmed by quantitative real-time RT-PCR; there was a high correlation between them. These results suggest that gene expression profiles may provide a useful method for evaluating drug sensitivity of cell lines and eliciting the underlying molecular mechanism. We further compared the genes identified from our current in vitro studies to the genes previously identified in our lab as regulated by APAP in both C57BL/6 and ICR mice in vivo. We found that a few genes are regulated in a similar pattern both in vivo and in vitro. These genes might be useful to develop as in vitro biomarkers for predicting in vivo hepatotoxicity. Based on our results, we suggest that gene expression profiles may provide useful information for elucidating the underlying molecular mechanisms of drug susceptibility and for evaluating drug sensitivity in vitro for extrapolation to in vivo.

• 한국컴퓨터정보학회논문지
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• 제15권12호
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• pp.197-207
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• 2010

대용량(High-throughput) 형태로 얻어진 cDNA 마이크로어레이 데이터에 다양한 데이터 마이닝 기법을 적용하면 서로 다른 조직에서 추출한 유전자의 발현정도를 비교할 수 있고 정상세포와 암세포에서 발현량의 차이를 보이는 DEG(Differently Expression Gene) 유전자를 추출할 수 있다. 이들을 이용하여 병을 진단할 수 있을 뿐만 아니라, 암의 진행 단계(Cancer Stage)에 따른 치료 방법을 결정할 수 있다. 마이크로어레이를 기반으로 한 대부분의 암 분류자는 기계학습 기법을 이용하여 암 관련 유전자를 추출하여, 이들 유전자를 총체적으로 이용하여 독립 샘플의 클래스(암, 정상)를 판정한다. 하지만 유전자의 발현량의 차이뿐만 아니라 유전자와 유전자의 상관관계의 변화가 질병 진단에 활용될 수 있다. 대부분의 질병은 단독 유전자의 변이에 의한 것이 아니라 유전자의 모듈로 이루어진 유전자조절네트워크의 변이에 의한 것이기 때문이다. 본 논문에서는 조건에 따라 특이적 관계를 나타내는 유전자 쌍을 식별하여, 이들 유전자 쌍을 이용한 유전자 분류 모듈을 생성한다. 분류 모듈을 이용한 암 분류 방법이 기존의 암 분류 방법보다 높은 정확도로 암과정상 샘플을 분류함을 보여주고 있다. 분류 모듈을 구성하는 유전자의 수가 상대적으로 적으므로 임상키트로의 개발도 고려할 수 있다. 향후 분류 모듈에 속하는 유전자의 기능적 검증을, GO(Gene Ontology)를 활용함으로서, 밝혀지지 않은 새로운 암 관련 유전자를 식별하고, 분류 모듈을 확대하여 암 특이적 유전자조절네트워크 구성에 활용할 계획이다.

• 응용통계연구
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• 제33권3호
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• pp.269-280
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• 2020

시간경로 유전자 발현 자료는 마이크로어레이 실험을 시간에 따라 관측한 대용량의 자료로 유전자 발현 수준을 동시에 파악할 수 있다. 하지만 실험 과정이 복잡하여 다양한 원인들에 의해 결측값이 자주 발생한다. 본 논문에서는 시간경로 유전자 발현 자료에 대한 결측값을 추정하는 방법으로 패턴 적응 최근접 이웃(pattern consistency index adaptive nearest neighbors; PANN) 방법을 제안하였다. 이 방법은 국소적 특징을 반영하는 적응 최근접 이웃(adaptive nearest neighbors; ANN) 방법과 관측 시점간 유전자 발현의 일치 정도를 고려하는 패턴일치지수를 결합시킨 것이다. 제안한 PANN 방법의 효능을 평가하기 위하여 두 가지의 실제 시간경로 자료들을 사용하여 몬테카를로 모의실험(Monte Carlo simulation study)을 시행하였다.

• 한국정보통신학회논문지
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• 제10권12호
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• pp.2283-2288
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• 2006

최근 생명 정보학 기술의 발달로 마이크로 단위의 실험조작이 가능해짐에 따라 하나의 chip상에서 전체 genome의 expression pattern을 관찰할 수 있게 되었고, 동시에 수 만개의 유전자들 간의 상호작용도 연구 가능하게 되었다. 이처럼 DNA 마이크로어레이 기술은 복잡한 생물체를 이해하는 새로운 방향을 제시해주게 되었다. 따라서 이러한 기술을 통해 얻어진 대량의 유전자 정보들을 효과적으로 분석하는 방법이 시급하다. 본 논문에서는 실험용 데이터로 하버드대학교의 바이오인포메틱스 코어 그룹의 샘플데이터 이용하여 마이크로어레이 실험에서 다양한 원인에 의해 발생하는 잡음(noise)을 줄이거나 제거하는 과정인 표준화 과정을 거쳐 특징 추출방법인 베이지안 알고리즘 ASA(Adaptive Simulated Annealing) 방법을 이용하여 데이터를 2개의 클래스로 나누고, 정확도를 평가하는 시스템을 설계하고 구현하였다. Lowess 표준화 후 98.23%의 정확도를 보였다.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2000년도 International Symposium on Bioinformatics
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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.

• Asian Pacific Journal of Cancer Prevention
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• 제14권7호
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• pp.4209-4214
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• 2013

Background: Breast cancer is among the five most common cancers and ranks first among cancers diagnosed in Iranian women. Screening and treatment of this disease with molecular methods, especially regarding high incidences at early age and advanced stage, is essential. Several genes with altered expression have been identified by cDNA microarray studies in breast cancer, with the Bcl-2 gene indicated as a likely candidate. In this study, we studied Bcl-2 gene expression levels in parallel tumor and non-tumor breast tissues. Materials and Methods: Forty samples including 21 tumor, 16 non tumor (marginal) and 3 benign breast tissues which were all pathologically diagnosed, were subjected to RNA extraction and polyA RT-PCR with the expression level of Bcl-2 quantified using real-time PCR. Results: There is higher expression levels of the Bcl-2 gene in tumor samples compared with marginal samples, but not attaining significance(p>0.05). Bcl-2 expression in 14 (66.7%) of the cases of tumor samples and 9 (56.3%) cases of the marginal samples were positive. Comparison of the expression of the Bcl-2 gene in histological grade showed that a high expression of Bcl-2 was associated with a high histological grade (p<0.41). Conclusions: Our data suggests that dysregulated Bcl-2 gene expression is potentially involved in the pathogenesis of breast cancer. Using gene expression analysis may significantly improve our ability for screening cancer patients and will prove a powerful tool in the diagnosis and prognostic evaluation of the disease whilst aiding the cooperative group trials in the Bcl-2 based therapy project.

• 응용통계연구
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• 제25권2호
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• pp.269-277
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• 2012

마이크로어레이 분석은 특이 발현하는 개별적인 유전자보다 유전자 온톨로지(Gene Ontology)와 같이 기능적 분류나 생물학적 경로(pathway)와 관련된 유전자군을 찾아내는 것이 그 해석의 용이성 때문에 최근 더욱 많은 연구가 진행되고 있다. 약물 처리에 의한 생물학적 반응을 연구할 때, 한 유전자군에 속하는 유전자들 각각의 특이 발현 여부의 유의성을 나타내는 $p$-value들을 취합하여 그 유전자군의 유의성을 결정하는 통계 검증 방법을 본 논문에서 소개하였다. 본 논문에 제시된 유전자군 분석(Gene group analysis) 방법은 Fisher's exact test나 permutation test와 같은 기존의 대표적인 방법들보다 더 정확하고 적용범위가 넓음을 실재 생물학 실험 자료의 분석을 통해 보였다. 제시된 유전자군 분석 방법은 SAS 프로그램으로 구현되었고 저자의 홈페이지(http://cafe.daum.net/go.analysis)에서 내려 받아 사용할 수 있다.

• 약학회지
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• 제51권3호
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• pp.179-185
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• 2007

Gastric cancer is one of the most common malignancies in Korea, but the predominant molecular event underlying gastric carcinogenesis remain unknown. Recently, DNA microarray technology has enabled the comprehensive analysis of gene expression level, and as such has yielded great insight into the molecular nature of cancer, However, despite the powerful approach of this techniques, the technical artifacts and/or bias in applied array platform limited the liability of resultant tens of thousand data points from microarray experiments. Therefore, we applied two different any platforms, such as olignucleotide microarray and cDNA microarray, to identify gastric cancer related large-scale molecular signature of the same human specimens. When thirty sets of matched human gastric cancer and normal tissues subjected to oligonucleotide microarray, total 623 genes were resulted as differently expressed genes in gastric cancer compared to normal tissues, and 252 genes for cDNA microarray analysis. In addition, forty three outlier genes which reflect the characteristic expression signature of gastric cancer beyond array platform and analytical protocol was recapitulated from two different expression profile. In conclusion, we were able to identify robust large-scale molecular changes in gastric cancer by applying two different platform of DNA microarray, this may facilitate to understand molecular carcinogenesis of gastric cancer.

• Communications for Statistical Applications and Methods
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• 제21권4호
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• pp.349-361
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• 2014

This paper compares of lasso type estimators in various high-dimensional data situations with sparse parameters. Lasso, adaptive lasso, fused lasso and elastic net as lasso type estimators and ridge estimator are compared via simulation in linear models with correlated and uncorrelated covariates and binary regression models with correlated covariates and discrete covariates. Each method is shown to have advantages with different penalty conditions according to sparsity patterns of regression parameters. We applied the lasso type methods to Arabidopsis microarray gene expression data to find the strongly significant genes to distinguish two groups.

• Asian Pacific Journal of Cancer Prevention
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• 제15권4호
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• pp.1783-1789
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• 2014

Background: The EMSY gene encodes a BRCA2-binding partner protein that represses the DNA repair function of BRCA2 in non-hereditary breast cancer. Although amplification of EMSY gene has been proposed to have prognostic value in breast cancer, no data have been available concerning EMSY tissue expression patterns and its associations with clinicopathological features. Materials and Methods: In the current study, we examined the expression and localization pattern of EMSY protein by immunohistochemistry and assessed its prognostic value in a well-characterized series of 116 unselected breast carcinomas with a mean follow up of 47 months using tissue microarray technique. Results: Immunohistochemical expression of EMSY protein was detected in 76% of primary breast tumors, localized in nuclear (18%), cytoplasmic (35%) or both cytoplasmic and nuclear sites (23%). Univariate analysis revealed a significant positive association between EMSY expression and lymph node metastasis (p value=0.045) and larger tumor size (p value=0.027), as well as a non-significant relation with increased risk of recurrence (p value=0.088), whereas no association with patients' survival (log rank test, p value=0.482), tumor grade or type was observed. Conclusions: Herein, we demonstrated for the first time the immunostaining pattern of EMSY protein in breast tumors. Our data imply that EMSY protein may have impact on clinicipathological parameters and could be considered as a potential target for breast cancer treatment.