Seon-Kyu Kim

Korea Research Institute of Bioscience and Biotechnology KRIBB, Anzan, Gyeonggi Province, South Korea

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Publications (16)80.89 Total impact

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    ABSTRACT: Because cancer has heterogeneous clinical behaviors due to the progressive accumulation of multiple genetic and epigenetic alterations, the identification of robust molecular signatures for predicting cancer outcome is profoundly important. Here, we introduce the APPEX web-based analysis platform as a versatile tool for identifying prognostic molecular signatures that predict cancer diversity. We incorporated most of statistical methods for survival analysis and implemented seven survival analysis workflows including CoxSingle, CoxMulti, IntransSingle, IntransMulti, SuperPC, TimeRoc, and multivariate. A total of 236 publicly available datasets were collected, processed, and stored to support easy independent validation of prognostic signatures. Two case studies including disease recurrence and bladder cancer progression were described using different combinations of the seven workflows. Availability and implementation: APPEX is freely available at http://www.appex.kr.
    Bioinformatics (Oxford, England). 08/2014;
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    ABSTRACT: Although standard treatment with transurethral resection and intravesical therapy (IVT) is known to be effective to address the clinical behavior of non-muscle-invasive bladder cancer (NMIBC), many patients fail to respond to the treatment and frequently experience disease recurrence. Here, we aim to identify a prognostic molecular signature that predicts the NMIBC heterogeneity and response to IVT. We analyzed the genomic profiles of 102 NMIBC patients to identify a signature associated with disease recurrence. The validity of the signature was verified in three independent patient cohorts (n = 658). Various statistical methods, including a leave-one-out cross-validation and multivariate Cox regression analyses, were applied to identify a signature. We confirmed an association between the signature and tumor aggressiveness with experimental assays using bladder cancer cell lines. Gene expression profiling in 102 NMIBC patients identified a CCNB1 signature associated with disease recurrence, which was validated in another three independent cohorts of 658 patients. The CCNB1 signature was shown to be an independent risk factor by a multivariate analysis and subset stratification according to stage and grade (HR 2.93, 95% CI = 1.302 to 6.594, P = 0.009). The subset analysis also revealed that the signature could identify patients who would benefit from IVT. Lastly, gene network analyses and experimental assays indicated that NMIBC recurrence could be mediated by FOXM1-CCNB1-Fanconi anemia pathways. The CCNB1 signature represents a promising diagnostic tool to identify NMIBC patients who have a high risk of recurrence and to predict response to IVT.
    Clinical Cancer Research 04/2014; · 7.84 Impact Factor
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    ABSTRACT: Colorectal cancer (CRC) patients frequently experience disease recurrence and distant metastasis. This study aimed to identify prognostic indicators, including individual responses to chemotherapy, in CRC patients. RNA-seq data was generated using 54 samples (normal colon, primary CRC, and liver metastases) from 18 CRC patients and genes associated with CRC aggressiveness were identified. A risk score based on these genes was developed and validated in four independent CRC patient cohorts (n = 1,063). Diverse statistical methods were applied to validate the risk scoring system, including a generalized linear model likelihood ratio test, Kaplan-Meier curves, a log-rank test, and the Cox model. TREM1 and CTGF were identified as two activated regulators associated with CRC aggressiveness. A risk score based on 19 genes regulated by TREM1 or CTGF activation (TCA19) was a significant prognostic indicator. In multivariate and subset analyses based on pathological staging, TCA19 was an independent risk factor (HR = 1.894, 95% CI = 1.227 – 2.809, P = 0.002). Subset stratification in stage III patients revealed that TCA19 had prognostic potential and identified patients who would benefit from adjuvant chemotherapy, regardless of age. The TCA19 predictor represents a novel diagnostic tool for identifying high-risk CRC patients and possibly predicting the response to adjuvant chemotherapy.
    Molecular Oncology. 01/2014;
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    ABSTRACT: DNA methylation patterns are associated with the development and prognosis of cancer. The aim of the present study was to identify novel methylation markers for the prediction of patient outcomes using microarray analysis of DNA methylation and RNA expression patterns in samples from long-term follow-up patients with non-muscle invasive bladder cancer (NMIBC). A total of 187 human bladder specimens were used for microarray array or pyrosequencing (PSQ) analyses: 6 normal controls (NC) and 181 NMIBC. Tumor-specific hypermethylated genes were selected from a data set comprising 24 matched microarray-based DNA methylation and gene expression profiles (6 controls and 18 NMIBC), and their clinical relevance was verified by quantitative PSQ analysis. The methylation status of Homeobox A9 (HOXA9), ISL LIM homeobox 1 (ISL1), and Aldehyde dehydrogenase 1 family, member A3 (ALDH1A3) was significantly associated with decreased gene expression levels and aggressive clinicopathological characteristics. Multivariate regression analyses showed that hypermethylation of these genes was an independent predictor of disease recurrence (HOXA9, ISL1, and ALDH1A3, either alone or in combination) and progression (ISL1 and ALDH1A3, either alone or in combination) (each p < 0.05). The results of the present study suggest that these novel methylation markers are independent prognostic indicators in NMIBC patients, which may facilitate the assessment of disease recurrence and progression in NMIBC patients and inform clinical decision making regarding treatment. © 2013 Wiley Periodicals, Inc.
    International Journal of Cancer 02/2013; · 6.20 Impact Factor
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    ABSTRACT: Long intergenic non-coding RNAs (lincRNAs) have historically been ignored in cancer biology. However, thousands of lincRNAs have been identified in mammals using recently developed genomic tools, including microarray and high-throughput RNA sequencing (RNA-seq). Several of the lincRNAs identified have been well characterized for their functions in carcinogenesis. Here we performed RNA-seq experiments comparing gastric cancer with normal tissues to find differentially expressed transcripts in intergenic regions. By analyzing our own RNA-seq and public microarray data, we identified 31 transcripts, including a known expressed sequence tag, BM742401. BM742401 was downregulated in cancer, and its downregulation was associated with poor survival in gastric cancer patients. Ectopic overexpression of BM742401 inhibited metastasis-related phenotypes and decreased the concentration of extracellular MMP9. These results suggest that BM742401 is a potential lincRNA marker and therapeutic target.
    Experimental & molecular medicine. 01/2013; 45:e31.
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    ABSTRACT: A total of 149 human prostate tissues obtained from our institute were assessed: 52 specimens of benign prostate hyperplasia (BPH) and 97 specimens of prostate cancer (PCa). The methylation status of the genes of Adenomatous polyposis coli (APC) and glutathione-S-transferase-P1 (GSTP1) was analyzed by quantitative pyrosequencing. A methylation score (M score) was calculated to capture the combined methylation level of both genes. The methylation level of each single gene and that of both genes combined was significantly higher in PCa specimens than in BPH (each p < 0.001). The value of APC methylation, GSTP1 methylation, and M score for predicting PCa was measured by the area under the receiver operating characteristic (ROC) curve and reached 0.954, 0.942, and 0.983, respectively. The sensitivity and specificity of the M score in discriminating between PCa and BPH reached 92.8% and 100.0%, respectively. The M score was positively associated with the serum prostate-specific antigen (PSA) level (p trend < 0.001). Our study demonstrates that the quantitative measurement of two methylation markers might drastically improve the ability to discriminate PCa from BPH.
    Journal of Biomolecular Screening 04/2012; 17(7):987-92. · 2.21 Impact Factor
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    ABSTRACT: We used gene expression profiling to identify inflammatory cytokines that correlate with bladder cancer development. Gene expression profiles of the tissue samples were investigated using cDNA microarrays that contained 103 non-muscle invasive bladder cancers (NMIBC), 62 muscle invasive bladder cancers (MIBC), 58 samples of histologically normal-looking surrounding tissues, and 10 normal, healthy subjects who served as the control cohort for comparison. We grouped the data-sets according to biological characterizations and focused on immune response genes with at least 2-fold differential expression in MIBC vs. controls. The experimental data-set identified 36 immune-related genes that were significantly altered in MIBC samples. In addition, 10 genes were up-regulated and 26 genes were down-regulated in MIBC samples compared with the normal tissues. Among the 10 up-regulated molecules examined, the capacity for both wound-healing migration and invasion was enhanced in response to IL-5, IL-20, and IL-28A in bladder cancer cell lines (253J and EJ cells), compared with untreated cells. The expression levels of IL-5, IL-20, and IL-28A were increased in patients with MIBC. All 3 cytokines and their receptors were produced in bladder cancer cell lines, as determined by real-time PCR, immunoblot analysis and confocal immunofluorescence. Up-regulation of MMP-2 and MMP-9 was found after IL-5, IL-20, and IL-28A stimulation in both cell types. Moreover, an EMSA assay showed that treatment with IL-5, IL-20, and IL-28A induced activation of the transcription factors NF-κB and AP-1 that regulate the MMP-9 promoter. Finally, activation of MAPK and Jak-Stat signaling was observed after the addition of IL-5, IL-20, and IL-28A to bladder cancer cells. This study suggests the presence of specific inflammatory cytokine (IL-5, IL-20, and IL-28A)-mediated association in bladder cancer development. All 3 cytokines may be important new molecular targets for the modulation of migration and invasion in bladder cancer.
    PLoS ONE 01/2012; 7(9):e40267. · 3.53 Impact Factor
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    ABSTRACT: Abnormal DNA methylation is associated with many human cancers. The aim of the present study was to identify novel methylation markers in prostate cancer (PCa) by microarray analysis and to test whether these markers could discriminate normal and PCa cells. Microarray-based DNA methylation and gene expression profiling was carried out using a panel of PCa cell lines and a control normal prostate cell line. The methylation status of candidate genes in prostate cell lines was confirmed by real-time reverse transcriptase-PCR, bisulfite sequencing analysis, and treatment with a demethylation agent. DNA methylation and gene expression analysis in 203 human prostate specimens, including 106 PCa and 97 benign prostate hyperplasia (BPH), were carried out. Further validation using microarray gene expression data from the Gene Expression Omnibus (GEO) was carried out. Epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1) was identified as a lead candidate methylation marker for PCa. The gene expression level of EFEMP1 was significantly higher in tissue samples from patients with BPH than in those with PCa (P < 0.001). The sensitivity and specificity of EFEMP1 methylation status in discriminating between PCa and BPH reached 95.3% (101 of 106) and 86.6% (84 of 97), respectively. From the GEO data set, we confirmed that the expression level of EFEMP1 was significantly different between PCa and BPH. Genome-wide characterization of DNA methylation profiles enabled the identification of EFEMP1 aberrant methylation patterns in PCa. EFEMP1 might be a useful indicator for the detection of PCa.
    Clinical Cancer Research 05/2011; 17(13):4523-30. · 7.84 Impact Factor
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    ABSTRACT: There are no reliable criteria to handle disease progression of muscle invasive bladder cancer (MIBC), which strongly influences patient survival. Therefore, an accurate predicting method to identify progressive MIBC patients is greatly needed. The aim of this study was to identify a genetic signature associated with disease progression in MIBC. To address this issue, we analyzed three independent cohorts (a training set, test set 1 and test set 2) comprising a total of 128 MIBC patients. Microarray gene expression profiling, including gene network analysis, was performed in the training set to identify a gene expression signature associated with disease progression. The prognostic value of the signature was validated in test set 1 and test set 2 by microarray and real-time reverse transcriptase polymerase chain reaction (RT-PCR), respectively. The determination of gene expression patterns by microarray data analysis identified 1,320 genes associated with disease progression. Gene network analysis of the 1,320 genes suggested that IL1B, S100A8, S100A9 and EGFR were important mediators of MIBC progression. We validated this putative four-gene signature in two independent cohorts (log-rank test, P < 0.05 each, respectively) and estimated the predictive value of the signature by multivariate Cox regression analysis (hazard ratio [HR], 6.24; 95% confidence interval [CI], 1.58-24.61; P = 0.009). Finally, signature-based stratification demonstrated that the four-gene signature was an independent predictor of MIBC progression. In conclusion, a molecular signature defined by four genes represents a promising diagnostic tool for the identification of MIBC patients at high risk of progression.
    Molecular Medicine 02/2011; 17(5-6):478-85. · 4.47 Impact Factor
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    ABSTRACT: Urinary bladder cancer is often a result of exposure to chemical carcinogens such as cigarette smoking. Because of histological similarity, chemically-induced rodent cancer model was largely used for human bladder cancer studies. Previous investigations have suggested that nicotinamide, water-soluble vitamin B3, may play a key role in cancer prevention through its activities in cellular repair. However, to date, evidence towards identifying the genetic alterations of nicotinamide in cancer prevention has not been provided. Here, we search for the molecular signatures of cancer prevention by nicotinamide using a N-butyl-N-(4-hydroxybutyl)-nitrosamine (BBN)-induced urinary bladder cancer model in mice. Via microarray gene expression profiling of 20 mice and 233 human bladder samples, we performed various statistical analyses and immunohistochemical staining for validation. The expression patterns of 893 genes associated with nicotinamide activity in cancer prevention were identified by microarray data analysis. Gene network analyses of these 893 genes revealed that the Myc and its associated genes may be the most important regulator of bladder cancer prevention, and the gene expression signature correlated well with protein expression data. Comparison of gene expression between human and mouse revealed that BBN-induced mouse bladder cancers exhibited gene expression profiles that were more similar to those of invasive human bladder cancers than to those of non-invasive human bladder cancers. This study demonstrates that nicotinamide plays an important role as a chemo-preventive and therapeutic agent in bladder cancer through the regulation of the Myc oncogenic signature. Nicotinamide may represent a promising therapeutic modality in patients with muscle-invasive bladder cancer.
    PLoS ONE 01/2011; 6(10):e26131. · 3.53 Impact Factor
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    ABSTRACT: In approximately 20% of patients with superficial bladder tumors, the tumors progress to invasive tumors after treatment. Current methods of predicting the clinical behavior of these tumors prospectively are unreliable. We aim to identify a molecular signature that can reliably identify patients with high-risk superficial tumors that are likely to progress to invasive tumors. Gene expression data were collected from tumor specimens from 165 patients with bladder cancer. Various statistical methods, including leave-one-out cross-validation methods, were applied to identify a gene expression signature that could predict the likelihood of progression to invasive tumors and to test the robustness of the expression signature in an independent cohort. The robustness of the gene expression signature was validated in an independent (n = 353) cohort. Supervised analysis of gene expression data revealed a gene expression signature that is strongly associated with invasive bladder tumors. A molecular classifier based on this gene expression signature correctly predicted the likelihood of progression of superficial tumor to invasive tumor. We present a molecular signature that can predict, at diagnosis, the likelihood of bladder cancer progression and, possibly, lead to improvements in patient therapy.
    Journal of Clinical Oncology 06/2010; 28(16):2660-7. · 18.04 Impact Factor
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    ABSTRACT: Intravesical Bacillus Calmette-Guérin (BCG) immunotherapy is effective in the prevention of recurrence and progression in many cases of nonmuscle invasive bladder cancer, but many patients fail to respond. The aim of this study was to identify gene sets of markers that could predict the response to BCG immunotherapy in primary pT1 bladder cancer using microarray gene expression profiling. We used 80 patients with primary pT1 bladder cancer treated with BCG immunotherapy as training (48) and test (32) sets. Microarray gene expression profiling was done in the training set to identify genes differentially expressed between responder and nonresponder to BCG immunotherapy according to the events (recurrence or progression). Using a real-time reverse-transcriptase PCR, our findings were validated in the test set. In the training set, 424 and 287 genes were significantly associated with recurrence- and progression-free survival, respectively. Functional annotation of these genes included cell-mediated immune response, inflammatory response, cellular growth, and proliferation. From these predictive gene signatures, 24 genes (12 in recurrence and 12 in progression) with the highest score of expression ratio were extracted for validation in the test set. In multivariate regression analyses, predictive gene signatures were the only independent predictors of recurrence (hazard ratio, 3.38; P = 0.048) or progression (hazard ratio, 10.49; P = 0.048) in the test set. Predictive gene signatures have diagnostic value for determining the response to intravesical BCG immunotherapy in primary pT1 bladder cancer.
    Clinical Cancer Research 03/2010; 16(7):2131-7. · 7.84 Impact Factor
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    ABSTRACT: While several molecular markers of bladder cancer prognosis have been identified, the limited value of current prognostic markers has created the need for new molecular indicators of bladder cancer outcomes. The aim of this study was to identify genetic signatures associated with disease prognosis in bladder cancer. We used 272 primary bladder cancer specimens for microarray analysis and real-time reverse transcriptase polymerase chain reaction (RT-PCR) analysis. Microarray gene expression analysis of randomly selected 165 primary bladder cancer specimens as an original cohort was carried out. Risk scores were applied to stratify prognosis-related gene classifiers. Prognosis-related gene classifiers were individually analyzed with tumor invasiveness (non-muscle invasive bladder cancer [NMIBC] and muscle invasive bladder cancer [MIBC]) and prognosis. We validated selected gene classifiers using RT-PCR in the original (165) and independent (107) cohorts. Ninety-seven genes related to disease progression among NMIBC patients were identified by microarray data analysis. Eight genes, a progression-related gene classifier in NMIBC, were selected for RT-PCR. The progression-related gene classifier in patients with NMIBC was closely correlated with progression in both original and independent cohorts. Furthermore, no patient with NMIBC in the good-prognosis signature group experienced cancer progression. We identified progression-related gene classifier that has strong predictive value for determining disease outcome in NMIBC. This gene classifier could assist in selecting NMIBC patients who might benefit from more aggressive therapeutic intervention or surveillance.
    Molecular Cancer 01/2010; 9:3. · 5.13 Impact Factor
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    ABSTRACT: S100 calcium binding protein A8 (S100A8) has been implicated as a prognostic indicator in several types of cancer. However, previous studies are limited in their ability to predict the clinical behavior of the cancer. Here, we sought to identify a molecular signature based on S100A8 expression and to assess its usefulness as a prognostic indicator of disease progression in non-muscle invasive bladder cancer (NMIBC). We used 103 primary NMIBC specimens for microarray gene expression profiling. The median follow-up period for all patients was 57.6 months (range: 3.2 to 137.0 months). Various statistical methods, including the leave-one-out cross validation method, were applied to identify a gene expression signature able to predict the likelihood of progression. The prognostic value of the gene expression signature was validated in an independent cohort (n = 302). Kaplan-Meier estimates revealed significant differences in disease progression associated with the expression signature of S100A8-correlated genes (log-rank test, P < 0.001). Multivariate Cox regression analysis revealed that the expression signature of S100A8-correlated genes was a strong predictor of disease progression (hazard ratio = 15.225, 95% confidence interval = 1.746 to 133.52, P = 0.014). We validated our results in an independent cohort and confirmed that this signature produced consistent prediction patterns. Finally, gene network analyses of the signature revealed that S100A8, IL1B, and S100A9 could be important mediators of the progression of NMIBC. The prognostic molecular signature defined by S100A8-correlated genes represents a promising diagnostic tool for the identification of NMIBC patients that have a high risk of progression to muscle invasive bladder cancer.
    BMC Cancer 01/2010; 10:21. · 3.33 Impact Factor
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    ABSTRACT: Gene Set Analyzer (GAzer) is a web-based integrated gene set analysis tool covering previously reported parametric and non-parametric models. Based on a simulation test for the reported algorithms, we classified and implemented three main statistical methods consisting of the z-statistic, gene permutation and sample permutation for ten gene set categories including Gene Ontology (GO) for human, mouse, rat and yeast. This tool identifies significantly altered gene sets scored by z-statistics and P-values from the z-test or permutation test and provides q-values and Bonferroni P-values to correct multiple hypothesis testing. GAzer allows users to observe changes in expression of each gene in a gene set or to see the significance of the gene sets containing a gene(s) of interest, thus allowing interactive data analysis both at the gene and gene set level. Moreover, GAzer offers extensive annotation for each gene. AVAILABILITY: The GAzer gene set analyzer is freely available at http://integromics.kobic.re.kr/GAzer/. SUPPLEMENTARY INFORMATION: This can be found on the web page (http://integromics.kobic.re.kr/GAzer/supplement.jsp).
    Bioinformatics 08/2007; 23(13):1697-9. · 5.47 Impact Factor
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    ABSTRACT: Genes are typically expressed in modular manners in biological processes. Recent studies reflect such features in analyzing gene expression patterns by directly scoring gene sets. Gene annotations have been used to define the gene sets, which have served to reveal specific biological themes from expression data. However, current annotations have limited analytical power, because they are classified by single categories providing only unary information for the gene sets. Here we propose a method for discovering composite biological themes from expression data. We intersected two annotated gene sets from different categories of Gene Ontology (GO). We then scored the expression changes of all the single and intersected sets. In this way, we were able to uncover, for example, a gene set with the molecular function F and the cellular component C that showed significant expression change, while the changes in individual gene sets were not significant. We provided an exemplary analysis for HIV-1 immune response. In addition, we tested the method on 20 public datasets where we found many 'filtered' composite terms the number of which reached approximately 34% (a strong criterion, 5% significance) of the number of significant unary terms on average. By using composite annotation, we can derive new and improved information about disease and biological processes from expression data. We provide a web application (ADGO: http://array.kobic.re.kr/ADGO) for the analysis of differentially expressed gene sets with composite GO annotations. The user can analyze Affymetrix and dual channel array (spotted cDNA and spotted oligo microarray) data for four species: human, mouse, rat and yeast. chu@kribb.re.kr http://array.kobic.re.kr/ADGO.
    Bioinformatics 10/2006; 22(18):2249-53. · 5.47 Impact Factor

Publication Stats

208 Citations
80.89 Total Impact Points

Institutions

  • 2006–2014
    • Korea Research Institute of Bioscience and Biotechnology KRIBB
      • • Medical Genomics Research Center
      • • Korean BioInformation Center
      Anzan, Gyeonggi Province, South Korea
  • 2013
    • Chungbuk National University
      • Department of Urology
      Tyundyu, North Chungcheong, South Korea
  • 2010
    • University of Texas MD Anderson Cancer Center
      Houston, Texas, United States