• Genomics & Informatics
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• 제19권1호
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• pp.10.1-10.7
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• 2021

Although many models have been proposed to accurately predict the response of drugs in cell lines recent years, understanding the genome related to drug response is also the key for completing oncology precision medicine. In this paper, based on the cancer cell line gene expression and the drug response data, we established a reliable and accurate drug response prediction model and found predictor genes for some drugs of interest. To this end, we first performed pre-selection of genes based on the Pearson correlation coefficient and then used ElasticNet regression model for drug response prediction and fine gene selection. To find more reliable set of predictor genes, we performed regression twice for each drug, one with IC₅₀ and the other with area under the curve (AUC) (or activity area). For the 12 drugs we tested, the predictive performance in terms of Pearson correlation coefficient exceeded 0.6 and the highest one was 17-AAG for which Pearson correlation coefficient was 0.811 for IC₅₀ and 0.81 for AUC. We identify common predictor genes for IC₅₀ and AUC, with which the performance was similar to those with genes separately found for IC₅₀ and AUC, but with much smaller number of predictor genes. By using only common predictor genes, the highest performance was AZD6244 (0.8016 for IC₅₀, 0.7945 for AUC) with 321 predictor genes.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2004년도 학술발표논문집
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• pp.195-198
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• 2004

One Important problem in a cancer microarray study is to identify a set of genes from which a molecular prognostic indicator can be developed. In parallel with this problem is to validate the chosen set of genes. We develop in this note a K-fold cross validation procedure by combining a 'pre-validation' technique and a bootstrap resampling procedure in the Cox regression . The pre-validation technique predicts the microarray predictor of a case without having seen the true class level of the case. It was suggested by Tibshirani and Efron (2002) to avoid the possible over-fitting in the regression in which a microarray based predictor is employed. The bootstrap resampling procedure for the Cox regression was proposed by Sauerbrei and Schumacher (1992) as a means of overcoming the instability of a stepwise selection procedure. We apply this K-fold cross validation to the microarray data of 92 gastric cancers of which the experiment was conducted at Cancer Metastasis Research Center, Yonsei University. We also share some of our experience on the 'false positive' result due to the information leak.

• BMB Reports
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• 제46권1호
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• pp.41-46
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• 2013

Identifying genes indispensable for an organism's life and their characteristics is one of the central questions in current biological research, and hence it would be helpful to develop computational approaches towards the prediction of essential genes. The performance of a predictor is usually measured by the area under the receiver operating characteristic curve (AUC). We propose a novel method by implementing genetic algorithms to maximize the partial AUC that is restricted to a specific interval of lower false positive rate (FPR), the region relevant to follow-up experimental validation. Our predictor uses various features based on sequence information, protein-protein interaction network topology, and gene expression profiles. A feature selection wrapper was developed to alleviate the over-fitting problem and to weigh each feature's relevance to prediction. We evaluated our method using the proteome of budding yeast. Our implementation of genetic algorithms maximizing the partial AUC below 0.05 or 0.10 of FPR outperformed other popular classification methods.

• Asian Pacific Journal of Cancer Prevention
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• 제15권10호
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• pp.4217-4224
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• 2014

Cholangiocarcinoma (CCA), a slow growing but highly metastatic tumor, is highly prevalent in Northeast Thailand. Specific tests that predict prognosis of CCA remain elusive. The present study was designed to investigate whether peripheral blood leukocyte (PBL) transcriptional profiles might be of use as a prognostic test in CCA patients. Gene expression profiles of PBLs from 9 CCA and 8 healthy subjects were conducted using the Affymetrix HG_U133 Plus 2.0 GeneChip. We indentified informative PBLs gene expression profiles that could reliably distinguish CCA patients from healthy subjects. Of these CCA specific genes, 117 genes were up regulated and 60 were down regulated. The molecular and cellular functions predicted for these CCA specific genes according to the Gene Ontology database indicated differential PBL expression of host immune response and tumor progression genes (EREG, TGF ${\beta}1$, CXCL2, CXCL3, IL-8, and VEGFA). The expression levels of 9 differentially expressed genes were verified in 36 CCA vs 20 healthy subjects. A set of three tumor invasion related genes (PLAU, CTSL and SERPINB2) computed as "prognostic index" was found to be an independent and statistically significant predictor for CCA patient survival. The present study shows that CCA PBLs may serve as disease predictive clinically accessible surrogates for indentifying expressed genes reflective of CCA disease severity.

• Asian Pacific Journal of Cancer Prevention
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• 제15권2호
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• pp.595-598
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• 2014

Background: NF-${\kappa}B$ inhibits apoptosis through induction of antiapoptotic proteins and suppression of proapoptotic genes. Various chemotherapy agents induce NF-${\kappa}B$ translocation and target gene activation. We conducted the present study to assess the predictive value of NF-${\kappa}B$ regarding pathologic responses after receiving neoadjuvant chemotherapy. Materials and Methods: We enrolled 131 patients with locally advanced invasive ductal breast carcinoma. Immunohistochemistry (IHC) was used to detect NF-${\kappa}B$ expression. Evaluation of pathologic response was elaborated with the Ribero classification. Results: Expression of NF-${\kappa}B$ was significantly associated with poor pathological response (p=0.02). From the multivariate analysis, it was found that the positive expression of NF-${\kappa}B$ yielded RR=1.74 (95%CI 0.77 to 3.94). Conclusions: NF-${\kappa}B$ can be used as a predictor of poor pathological response after neoadjuvant chemotherapy.

• Toxicological Research
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• 제32권4호
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• pp.289-300
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• 2016

Non-genotoxic carcinogens are substances that induce tumorigenesis by non-mutagenic mechanisms and long term rodent bioassays are required to identify them. Recent studies have shown that transcription profiling can be applied to develop early identifiers for long term phenotypes. In this study, we used rat liver expression profiles from the NTP (National Toxicology Program, Research Triangle Park, USA) DrugMatrix Database to construct a gene classifier that can distinguish between non-genotoxic carcinogens and other chemicals. The model was based on short term exposure assays (3 days) and the training was limited to oxidative stressors, peroxisome proliferators and hormone modulators. Validation of the predictor was performed on independent toxicogenomic data (TG-GATEs, Toxicogenomics Project-Genomics Assisted Toxicity Evaluation System, Osaka, Japan). To build our model we performed Random Forests together with a recursive elimination algorithm (VarSelRF). Gene set enrichment analysis was employed for functional interpretation. A total of 770 microarrays comprising 96 different compounds were analyzed and a predictor of 54 genes was built. Prediction accuracy was 0.85 in the training set, 0.87 in the test set and increased with increasing concentration in the validation set: 0.6 at low dose, 0.7 at medium doses and 0.81 at high doses. Pathway analysis revealed gene prominence of cellular respiration, energy production and lipoprotein metabolism. The biggest target of toxicogenomics is accurately predict the toxicity of unknown drugs. In this analysis, we presented a classifier that can predict non-genotoxic carcinogenicity by using short term exposure assays. In this approach, dose level is critical when evaluating chemicals at early time points.

• 한국식품영양과학회지
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• 제42권12호
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• pp.1899-1907
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• 2013

복분자 미숙과 물추출물이 콜레스테롤 개선에 미치는 영향을 측정한 결과는 다음과 같다. 간세포주(HepG2 cells)에서 복분자 미숙과 물추출물은 SREBPs를 증가시킴으로써 혈액 내에 LDL을 LDL receptor를 통해서 세포 안으로 흡수시키고, 콜레스테롤 합성에 관여하는 HMG-CoA reductase 활성을 억제하면서 체내 콜레스테롤을 조절하였다. 그러나 HDL의 생성에 관여하는 유전자(ABCA1, SR-B1)는 변화를 보이지 않았다. 결과적으로 복분자 미숙과 물추출물이 LDL receptor를 통해서 LDL을 억제시키고 체내에서는 콜레스테롤 생합성을 억제하였으며, HDL의 생성에는 관여를 하지 않음을 확인하였다. 또한 ApoB1/ApoA1 ratio 값을 통해서 동맥경화 지표를 확인해 본 결과 유의성 있게 수치가 감소함을 확인하였고, 이는 미숙과 물추출물이 콜레스테롤을 개선하여 동맥경화를 예방할 것으로 기대한다. 또한 대식세포(RAW 264.7 cells)에서 복분자 미숙과 물추출물이 CD 36, SR-A 수용체를 억제시킴으로 인해 세포 내의 ox-LDL 의 흡수를 차단시키고, 세포 안에서는 macrophage에 있는 PPAR-${\gamma}$를 억제시킴으로 인해 LDL 산화가 억제되었다. Adipophilin의 활성이 억제됨에 따라 세포 안에 있는 콜레스테롤 방출을 촉진시킴으로 인해 동맥경화를 완화시킬 수 있다고 사료된다.

• Asian Pacific Journal of Cancer Prevention
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• 제15권3호
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• pp.1255-1262
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• 2014

Background: The aim of the study was to investigate any associations between benign prostate hyperplasia (BPH) and single nucleotide polymorphisms (SNPs) in the VDR gene (FokI, BsmI, ApaI and Taq${\alpha}$I loci) and the CYP17 gene (MspA1I locus), as well as TA repeat polymorphism in SRD5A2 gene among Lebanese men. Materials and Methods: DNA extracted from blood of 68 subjects with confirmed BPH and 79 age-matched controls was subjected to PCR/PCR-restriction fragment length polymorphism analysis. The odds ra=tio (OR) of having a genotype and the relative risk (RR) of developing BPH for having the genotype were calculated and the alleles were designated risk-bearing or protective. Results: Our data indicated that the A and B alleles of the VDR ApaI and BsmI SNPs were highly associated with increased risk of BPH (p=0.0168 and 0.0002, respectively). Moreover, 63% of the controls compared to 43% of the subjects with BPH were homozygous for none of the risk-bearing alleles (p=0.0123) whereas 60% of the controls and 28% of the subjects with BPH were homozygous for two or more protective alleles (p<0.0001). Conclusions: For the first time, our study demonstrated that ApaI and BsmI of the VDR gene are associated with risk of BPH among Lebanese men. Our study also indicated that overall polymorphism profile of all the genes involved in prostate physiology could be a better predictor of BPH risk.

• Asian Pacific Journal of Cancer Prevention
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• 제13권3호
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• pp.1053-1057
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• 2012

Objective: Identifying cancer-related genes or proteins is critical in preventing and controlling colorectal cancer (CRC). This study was to investigate the clinicopathological and prognostic value of activating transcription factor 1 (ATF1) in CRC. Methods: Protein expression of ATF1 was detected using immunohistochemistry in 66 CRC tissues. Clinicopathological association of ATF1 in CRC was analyzed with chi-square test or Fisher's exact test. The prognostic value of ATF1 in CRC is estimated using the Kaplan-Meier analysis and Cox regression models. Results: The ATF1 protein expression was significantly lower in tumor tissues than corresponding normal tissues (51.5% and 71.1%, respectively, P = 0.038). No correlation was found between ATF1 expression and the investigated clinicopathological parameters, including gender, age, depth of invasion, lymph node status, metastasis, pathological stage, vascular tumoral emboli, peritumoral deposits, chemotherapy and original tumor site (all with P > 0.05). Patients with higher ATF1 expression levels have a significantly higher survival rate than that with lower expression (P = 0.026 for overall survival, P = 0.008 for progress free survival). Multivariate Cox regression model revealed that ATF1 expression and depth of invasion were the predictors of the overall survival (P = 0.008 and P = 0.028) and progress free survival (P = 0.002 and P = 0.005) in CRC. Conclusions: Higher ATF1 expression is a predictor of a favorable outcome for the overall survival and progress free survival in CRC.

• 생물정신의학
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• 제15권1호
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• pp.14-22
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• 2008

우울 장애는 유전적 요인과 함께 환경적 요인이 복합적으로 작용하는 정신 장애이다. 본 연구에서는 세로토닌 체계와 연관된 유전적 요인과 생활사건과 같은 환경적 요인이 초기 성인기 우울 장애 발현에 미치는 영향을 조사함으로써 우울 장애의 원인론에 있어 유전자${\times}$환경 상호작용을 설명할 수 있는 자료를 제시하고자 하였다. 534명의 대학 신입생을 종적으로 추적 조사하여 생활사건 빈도와 중요도, 우울 척도와 불안 척도를 조사하였으며 전화 면담을 통해 DSM-IV 우울 장애 여부를 확인하였다. 최종적으로 150명이 연구에 포함되었으며 이전 연구로 확인된 TPH1 유전형과 함께 보관되어 있던 대상군의 DNA를 이용하여 SNaPshot$^{TM}$ 방식으로 TPH2, 5HTR2A 유전자를 추가 분석하였다. 유전자 정보와 생활사건 특성이 우울 증상에 미치는 영향을 확인하기 위해 로지스틱 회귀 분석과 상관 분석, 카이 자승 분석을 사용하였다. TPH1 유전형 중 C 대립 유전자가 존재하지 않는 집단과 달리 C 대립 유전자가 존재하는 집단에서는 생활사건 빈도가 우울 장애 유발에 유의한 영향을 미쳤다. 이러한 영향은 다른 대립 유전자나 유전형을 보이는 집단에서는 관찰되지 않았다. 본 연구의 결과는 TPH1 유전형은 생활사건 이후 우울 장애 발생의 유의미한 예측 요인임을 시사한다. 이는 우울 장애의 유전${\times}$환경 상호작용에 TPH1 유전자가 작용하고 있음을 제시한다.