Eric Y Chuang

University of Texas at San Antonio, San Antonio, TX, United States

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Publications (62)270.19 Total impact

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    ABSTRACT: Numerous efforts have been made to elucidate the etiology and improve the treatment of lung cancer, but the overall five-year survival rate is still only 15%. Although cigarette smoking is the primary risk factor for lung cancer, only 7% of female lung cancer patients in Taiwan have a history of smoking. Since cancer results from progressive accumulation of genetic aberrations, genomic rearrangements may be early events in carcinogenesis. In order to identify biomarkers of early-stage adenocarcinoma, the genome-wide DNA aberrations of 60 pairs of lung adenocarcinoma and adjacent normal lung tissue in non-smoking women were examined using Affymetrix Genome-Wide Human SNP 6.0 arrays. Common copy number variation (CNV) regions were identified by >=30% of patients with copy number beyond 2 +/- 0.5 of copy numbers for each single nucleotide polymorphism (SNP) and at least 100 continuous SNP variant loci. SNPs associated with lung adenocarcinoma were identified by McNemar's test. Loss of heterozygosity (LOH) SNPs were identified in >=18% of patients with LOH in the locus. Aberration of SNP rs10248565 at HDAC9 in chromosome 7p21.1 was identified from concurrent analyses of CNVs, SNPs, and LOH. The results elucidate the genetic etiology of lung adenocarcinoma by demonstrating that SNP rs10248565 may be a potential biomarker of cancer susceptibility.
    Journal of Biomedical Science 03/2014; 21(1):24. · 2.46 Impact Factor
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    ABSTRACT: Lung cancer is the leading cause of cancer death worldwide, and brain metastasis is a major cause of morbidity and mortality in lung cancer. CDH2 (N-cadherin, a mesenchymal marker of the epithelial-mesenchymal transition) and ADAM9 (a type I transmembrane protein) are related to lung cancer brain metastasis; however, it is unclear how they interact to mediate this metastasis. Because microRNAs regulate many biological functions and disease processes (e.g., cancer) by down-regulating their target genes, microRNA microarrays were used to identify ADAM9-regulated miRNAs that target CDH2 in aggressive lung cancer cells. Luciferase assays and western blot analysis showed that CDH2 is a target gene of miR-218. MiR-218 was generated from pri-mir-218-1, which is located in SLIT2, in non-invasive lung adenocarcinoma cells, whereas its expression was inhibited in aggressive lung adenocarcinoma. The down-regulation of ADAM9 up-regulated SLIT2 and miR-218, thus down-regulating CDH2 expression. This study revealed that ADAM9 activates CDH2 through the release of miR-218 inhibition on CDH2 in lung adenocarcinoma.
    PLoS ONE 01/2014; 9(4):e94065. · 3.73 Impact Factor
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    ABSTRACT: Brugada syndrome (BrS) is an inheritable sudden cardiac death disease mainly caused by SCN5A mutations. Traditional approaches can be costly and time-consuming if all candidate variants need to be validated through in vitro studies. Therefore, we developed a new approach by combining multiple in silico analyses to predict functional and structural changes of candidate SCN5A variants in BrS before conducting in vitro studies. Five SCN5A non-synonymous variants (1651G>A, 1776C>G, 1673A>G, 3269C>T and 3578G>A) were identified in 14 BrS patients using direct DNA sequencing. Several bioinformatics algorithms were applied and predicted that 1651G>A (A551T) and 1776C>G (N592K) were high-risk SCN5A variants (odds ratio 59.59 and 23.93). The results were validated by Mass spectrometry and in vitro electrophysiological assays. We concluded that integrating sequence-based information and secondary protein structures elements may help select highly potential variants in BrS before conducting time-consuming electrophysiological studies and two novel SCN5A mutations were validated.
    Scientific Reports 01/2014; 4:3850. · 2.93 Impact Factor
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    ABSTRACT: DNA methylation plays an important role in regulating cell growth and disease development. Methylation profiles are examined by bisulfite conversion; however, the lack of markers for bisulfite conversion efficiency and appropriate internal control genes remains a major challenge. To address these issues, we utilized two bioinformatics approaches, coefficients of variances and resampling tests, to identify probes showing stable methylation levels from several independent microarray datasets. Mass spectrometry validated the consistently high methylation levels of the five probes (N4BP2, EGFL8, CTRB1, TSPAN3, and ZNF690) in 13 human tissue types from 24 cell lines. Linear associations between detected methylation levels and methyl concentrations of DNA samples were further demonstrated in three genes (N4BP2, EGFL8, and CTRB1). To summarize, we identified five genes which may serve as internal controls for methylation studies by analyzing large-scale microarray data, and three of them can be used as markers for evaluating the efficiency of bisulfite conversion.
    Scientific Reports 01/2014; 4:4351. · 2.93 Impact Factor
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    Tzu-Pin Lu, Eric Y Chuang, James J Chen
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    ABSTRACT: Lung cancer is the leading cause of cancer-related death worldwide. Tremendous research efforts have been devoted to improving treatment procedures, but the average five-year overall survival rates are still less than 20%. Many biomarkers have been identified for predicting survival; challenges arise, however, in translating the findings into clinical practice due to their inconsistency and irreproducibility. In this study, we proposed an approach by identifying predictive genes through pathways. The microarrays from Shedden et al. were used as the training set, and the log-rank test was performed to select potential signature genes. We focused on 24 cancer-related pathways from 4 biological databases. A scoring scheme was developed by the Cox hazard regression model, and patients were divided into two groups based on the medians. Subsequently, their predictability and generalizability were evaluated by the 2-fold cross-validation and a resampling test in 4 independent datasets, respectively. A set of 16 genes related to apoptosis execution was demonstrated to have good predictability as well as generalizability in more than 700 lung adenocarcinoma patients and was reproducible in 4 independent datasets. This signature set was shown to have superior performances compared to 6 other published signatures. Furthermore, the corresponding risk scores derived from the set were found to associate with the efficacy of the anti-cancer drug ZD-6474 targeting EGFR. In summary, we presented a new approach to identify reproducible survival predictors for lung adenocarcinoma, and the identified genes may serve as both prognostic and predictive biomarkers in the future.
    BMC Bioinformatics 12/2013; 14(1):371. · 3.02 Impact Factor
  • I-J Wang, S-L Chen, T-P Lu, E Y Chuang, P-C Chen
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    ABSTRACT: The biological mechanisms of how prenatal smoke exposure leading to atopic disorders remain to be addressed. Whether prenatal smoke exposure affects DNA methylation leading to atopic disorders is not clear. As most children suffering from atopic dermatitis (AD) continue to develop asthma later in life, we explored whether prenatal smoke exposure induces cord blood DNA methylation. Methylation differences associated with smoke exposure were screened by Illumina Infinium 27K methylation arrays for 14 children from the Taiwan birth panel study cohort initially. Information about development of atopic dermatitis (AD) and risk factors was collected. Cord blood cotinine levels were measured to represent prenatal smoke exposure. CpG loci that demonstrated a statistically significant difference in methylation were validated by methylation-dependent fragment separation (MDFS). Differential methylation in three genes (TSLP, GSTT1, and CYB5R3) was identified through the screen. Among these, only thymic stromal lymphopoietin (TSLP) gene displayed significant difference in promoter methylation percentage after being validated by MDFS (p = 0.018). TSLP gene was further investigated in a larger sample of 150 children from the cohort who completed the follow-up study. Methylation status of the TSLP 5'-CpG island (CGI) was found to be significantly associated with prenatal smoke exposure (OR=3.17, 95% CI=1.63-6.19) and with AD (OR=2.32, 95% CI=1.06-5.11). The degree of TSLP 5'CGI methylation inversely correlated with TSLP protein expression levels (r = -0.45, P = 0.001). CONCLUSIONS & CLINICAL RELEVANCE: The effect of prenatal tobacco smoke exposure on the risk for AD may be mediated through DNA methylation.
    Clinical & Experimental Allergy 05/2013; 43(5):535-43. · 4.79 Impact Factor
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    ABSTRACT: Multiclass prediction remains an obstacle for high-throughput data analysis such as microarray gene expression profiles. Despite recent advancements in machine learning and bioinformatics, most classification tools were limited to the applications of binary responses. Our aim was to apply partial least square (PLS) regression for breast cancer intrinsic taxonomy, of which five distinct molecular subtypes were identified. The PAM50 signature genes were used as predictive variables in PLS analysis, and the latent gene component scores were used in binary logistic regression for each molecular subtype. The 139 prototypical arrays for PAM50 development were used as training dataset, and three independent microarray studies with Han Chinese origin were used for independent validation (n = 535). The agreement between PAM50 centroid-based single sample prediction (SSP) and PLS-regression was excellent (weighted Kappa: 0.988) within the training samples, but deteriorated substantially in independent samples, which could attribute to much more unclassified samples by PLS-regression. If these unclassified samples were removed, the agreement between PAM50 SSP and PLS-regression improved enormously (weighted Kappa: 0.829 as opposed to 0.541 when unclassified samples were analyzed). Our study ascertained the feasibility of PLS-regression in multi-class prediction, and distinct clinical presentations and prognostic discrepancies were observed across breast cancer molecular subtypes.
    BioMed research international. 01/2013; 2013:248648.
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    ABSTRACT: Recent studies indicate that both genomic alterations and transcriptional dysregulation influence the disease progresses. This study proposes a method identifying pathways by integrating copy numbers (CN), gene expressions (GE) and their correlations. A lung cancer patients dataset with both normal and tumor tissues is utilized to evaluate the performance of the proposed method. To further appraise the predicting abilities of those pathways, these patients are classified by support vector machines. Based on the classification results, pathways integrating CN, GE and their correlations is more informative and biologically meaningful and perform better than pathways obtained by only CN or only GE.
    International Journal of Data Mining and Bioinformatics 01/2013; 8(1):92-104. · 0.39 Impact Factor
  • E.Y. Chuang
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    ABSTRACT: With the expansion of available high-throughput genomic technologies such as DNA microarray and next generation sequencing (NGS) in the past two decades, knowing how to use appropriate software tools running on powerful computers is a necessity for biologists/physicians to identify new genes or targets. Thus, bioinformaticians have been developing many user-friendly analytical tools/systems; those tools/systems enable researchers to efficiently analyze massive genomic data and select genes with modulated expression patterns or altered characters. Based on the modulated genes identified from genomic analyses, researchers can further analyze and investigate possible regulatory mechanisms of human genes and diseases in order to discover potential therapeutic targets or predictive biomarkers. In my talk, I will present some bioinformatic tools which were developed in my lab for processing, analyzing and interpreting genomic data. In addition, I will provide a few studies to demonstrate how we utilized different analytical tools to identify new molecular signatures or predictive biomarkers in various cancers.
    Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME), 2013 3rd International Conference on; 01/2013
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    ABSTRACT: Macrophages play a pivotal role in the immune system through recognition and elimination of microbial pathogens. Toll-like receptors (TLRs) on macrophages interact with microbial substances and initiate signal transduction through intracellular adapters. TLR4, which recognizes the lipopolysaccharides (LPS) on Gram-positive and Gram-negative bacteria, triggers downstream signaling mediators and eventually activates IκB kinase (IKK) complex and mitogen-activated protein kinases (MAPKs) such as p38. Previous reports revealed that, in addition to NF-κB, a core transcription factor of the innate immune response, the induction of some LPS-induced genes in macrophages required another transcription factor whose activity depends on p38. However, these additional transcription factors remain to be identified. In order to identify p38-activated transcription factors that cooperate with NF-κB in response to LPS stimulation, microarrays were used to identify genes regulated by both NF-κB and p38 using wild-type, IKK-depleted, and p38 inhibitor-treated mouse bone marrow-derived macrophages (BMDMs). In silico analysis of transcription factor binding sites was used to predict the potential synergistic transcription factors from the co-expressed genes. Among these genes, NF-κB and C/EBPβ, a p38 downstream transcription factor, were predicted to co-regulate genes in LPS-stimulated BMDMs. Based on the subsequent results of a chromatin immunoprecipitation assay and TNFAIP3 expression in C/EBPβ-ablated macrophages, we demonstrated that Tnfaip3 is regulated by both NF-κB and p38-dependent C/EBPβ. These results identify a novel regulatory mechanism in TLR4-mediated innate immunity.
    PLoS ONE 01/2013; 8(9):e73153. · 3.73 Impact Factor
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    ABSTRACT: Lung cancer is the leading cause of cancer-related mortality worldwide. Radiotherapy is often applied for treating lung cancer, but it often fails because of the relative non-susceptibility of lung cancer cells to radiation. MicroRNAs (miRNAs) have been reported to modulate the radiosensitivity of lung cancer cells and have the potential to improve the efficacy of radiotherapy. The purpose of this study was to identify a miRNA that can adjust radiosensitivity in lung adenocarcinoma cells. Two lung adenocarcinoma cell lines (CL1-0 and CL1-5) with different metastatic ability and radiosensitivity were used. In order to understand the regulatory mechanisms of differential radiosensitivity in these isogenic tumor cells, both CL1-0 and CL1-5 were treated with 10 Gy radiation, and were harvested respectively at 0, 1, 4, and 24 h after radiation exposure. The changes in expression of miRNA upon irradiation were examined using Illumina Human microRNA BeadChips. Twenty-six miRNAs were identified as having differential expression post-irradiation in CL1-0 or CL1-5 cells. Among these miRNAs, miR-449a, which was down-regulated in CL1-0 cells at 24 h after irradiation, was chosen for further investigation. Overexpression of miR-449a in CL1-0 cells effectively increased irradiation-induced DNA damage and apoptosis, altered the cell cycle distribution and eventually led to sensitization of CL1-0 to irradiation.
    PLoS ONE 01/2013; 8(4):e62383. · 3.73 Impact Factor
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    ABSTRACT: The interplay between copy number variation (CNV) and differential gene expression may be able to shed light on molecular process underlying breast cancer and lead to the discovery of cancer-related genes. In the current study, genes concurrently identified in array comparative genomic hybridization (CGH) and gene expression microarrays were used to derive gene signatures for Han Chinese breast cancers. We performed 23 array CGHs and 81 gene expression microarrays in breast cancer samples from Taiwanese women. Genes with coherent patterns of both CNV and differential gene expression were identified from the 21 samples assayed using both platforms. We used these genes to derive signatures associated with clinical ER and HER2 status and disease-free survival. DISTRIBUTIONS OF SIGNATURE GENES WERE STRONGLY ASSOCIATED WITH CHROMOSOMAL LOCATION: chromosome 16 for ER and 17 for HER2. A breast cancer risk predictive model was built based on the first supervised principal component from 16 genes (RCAN3, MCOLN2, DENND2D, RWDD3, ZMYM6, CAPZA1, GPR18, WARS2, TRIM45, SCRN1, CSNK1E, HBXIP, CSDE1, MRPL20, IKZF1, and COL20A1), and distinct survival patterns were observed between the high- and low-risk groups from the combined dataset of 408 microarrays. The risk score was significantly higher in breast cancer patients with recurrence, metastasis, or mortality than in relapse-free individuals (0.241 versus 0, P<0.001). The concurrent gene risk predictive model remained discriminative across distinct clinical ER and HER2 statuses in subgroup analysis. Prognostic comparisons with published gene expression signatures showed a better discerning ability of concurrent genes, many of which were rarely identifiable if expression data were pre-selected by phenotype correlations or variability of individual genes. We conclude that parallel analysis of CGH and microarray data, in conjunction with known gene expression patterns, can be used to identify biomarkers with prognostic values in breast cancer.
    PLoS ONE 01/2013; 8(10):e76421. · 3.73 Impact Factor
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    ABSTRACT: Common microarray and next-generation sequencing data analysis concentrate on tumor subtype classification, marker detection, and transcriptional regulation discovery during biological processes by exploring the correlated gene expression patterns and their shared functions. Genetic regulatory network (GRN) based approaches have been employed in many large studies in order to scrutinize for dysregulation and potential treatment controls. In addition to gene regulation and network construction, the concept of the network modulator that has significant systemic impact has been proposed, and detection algorithms have been developed in past years. Here we provide a unified mathematic description of these methods, followed with a brief survey of these modulator identification algorithms. As an early attempt to extend the concept to new RNA regulation mechanism, competitive endogenous RNA (ceRNA), into a modulator framework, we provide two applications to illustrate the network construction, modulation effect, and the preliminary finding from these networks. Those methods we surveyed and developed are used to dissect the regulated network under different modulators. Not limit to these, the concept of "modulation" can adapt to various biological mechanisms to discover the novel gene regulation mechanisms.
    Advances in Bioinformatics 01/2013; 2013:360678.
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    ABSTRACT: Breast cancer is a heterogeneous disease in terms of transcriptional aberrations; moreover, microarray gene expression profiles had defined 5 molecular subtypes based on certain intrinsic genes. This study aimed to evaluate the prediction consistency of breast cancer molecular subtypes from 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50) as well as clinical presentations of each molecualr subtype in Han Chinese population. In all, 169 breast cancer samples (44 from Taiwan and 125 from China) of Han Chinese population were gathered, and the gene expression features corresponding to 3 distinct intrinsic gene sets (Sørlie 500, Hu 306 and PAM50) were retrieved for molecular subtype prediction. For Sørlie 500 and Hu 306 intrinsic gene set, mean-centring of genes and distance-weighted discrimination (DWD) remarkably reduced the number of unclassified cases. Regarding pairwise agreement, the highest predictive consistency was found between Hu 306 and PAM50. In all, 150 and 126 samples were assigned into identical subtypes by both Hu 306 and PAM50 genes, under mean-centring and DWD. Luminal B tended to show a higher nuclear grade and have more HER2 over-expression status than luminal A did. No basal-like breast tumours were ER positive, and most HER2-enriched breast tumours showed HER2 over-expression, whereas, only two-thirds of ER negativity/HER2 over-expression tumros were predicted as HER2-enriched molecular subtype. For 44 Taiwanese breast cancers with survival data, a better prognosis of luminal A than luminal B subtype in ER-postive breast cancers and a better prognosis of basal-like than HER2-enriched subtype in ER-negative breast cancers was observed. We suggest that the intrinsic signature Hu 306 or PAM50 be used for breast cancers in the Han Chinese population during molecular subtyping. For the prognostic value and decision making based on intrinsic subtypes, further prospective study with longer survival data is needed.
    Journal of Translational Medicine 09/2012; 10 Suppl 1:S10. · 3.46 Impact Factor
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    ABSTRACT: Liver cirrhosis is a critical state in the natural course of hepatocellular carcinoma (HCC). We sought to investigate the potential of in-depth proteomics to reveal plasma protein signatures that reflect common networks/pathways of liver cirrhosis, and to determine whether the cirrhosis-related signature in plasma is linked to the development of HCC among hepatitis B virus (HBV) carriers. We first compared plasma protein profiles using a 174-antibody microarray system between three groups of HBV carriers with different Child's grades of cirrhosis, which revealed a panel of 45 differentially expressed proteins with a high accuracy for discriminating Child's B/C. Ingenuity Pathway Analysis identified two main up-regulated networks connecting the 45 proteins that were most enriched for genes in the pathway of hepatic stellate cell activation. A parsimonious subset of 11 pathway-based proteins was then selected for quantification to correlate with HCC risk among 49 HCC cases and 50 controls in a nested case-control study within a 16-yr follow-up cohort of HBV carriers. A high risk score derived from a principal component analysis, which was used to extract the cluster structure of the 11 proteins, was associated with HCC (odds ratio = 4.83, 95% confidence interval: 1.26-18.56) even after adjustment for viral and clinical variables, implying the involvement of a pattern of coordinated proteins. Stepwise logistic regression on the 11 proteins revealed ICAM-2 as an independent predictor for HCC. These findings may give further insight into the pathobiology of hepatocarcinogenesis, allow testing of the cirrhosis-related plasma protein signature as a potential predictive biomarker for HCC. © 2012 Wiley Periodicals, Inc.
    Molecular Carcinogenesis 08/2012; · 4.27 Impact Factor
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    ABSTRACT: Many prediction tools for microRNA (miRNA) targets have been developed, but inconsistent predictions were observed across multiple algorithms, which can make further analysis difficult. Moreover, the nomenclature of human miRNAs changes rapidly. To address these issues, we developed a web-based system, miRSystem, for converting queried miRNAs to the latest annotation and predicting the function of miRNA by integrating miRNA target gene prediction and function/pathway analyses. First, queried miRNA IDs were converted to the latest annotated version to prevent potential conflicts resulting from multiple aliases. Next, by combining seven algorithms and two validated databases, potential gene targets of miRNAs and their functions were predicted based on the consistency across independent algorithms and observed/expected ratios. Lastly, five pathway databases were included to characterize the enriched pathways of target genes through bootstrap approaches. Based on the enriched pathways of target genes, the functions of queried miRNAs could be predicted. MiRSystem is a user-friendly tool for predicting the target genes and their associated pathways for many miRNAs simultaneously. The web server and the documentation are freely available at http://mirsystem.cgm.ntu.edu.tw/.
    PLoS ONE 01/2012; 7(8):e42390. · 3.73 Impact Factor
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    ABSTRACT: Triple-negative breast cancer is a subtype of breast cancer with aggressive tumor behavior and distinct disease etiology. Due to the lack of an effective targeted medicine, treatment options for triple-negative breast cancer are few and recurrence rates are high. Although various multi-gene prognostic markers have been proposed for the prediction of breast cancer outcome, most of them were proven clinically useful only for estrogen receptor-positive breast cancers. Reliable identification of triple-negative patients with a favorable prognosis is not yet possible. Clinicopathological information and microarray data from 157 invasive breast carcinomas were collected at National Taiwan University Hospital from 1995 to 2008. Gene expression data of 51 triple-negative and 106 luminal breast cancers were generated by oligonucleotide microarrays. Hierarchical clustering analysis revealed that the majority (94%) of triple-negative breast cancers were tightly clustered together carrying strong basal-like characteristics. A 45-gene prognostic signature giving 98% predictive accuracy in distant recurrence of our triple-negative patients was determined using the receiver operating characteristic analysis and leave-one-out cross validation. External validation of the prognostic signature in an independent microarray dataset of 59 early-stage triple-negative patients also obtained statistical significance (hazard ratio 2.29, 95% confidence interval (CI) 1.04-5.06, Cox P = 0.04), outperforming five other published breast cancer prognostic signatures. The 45-gene signature identified in this study revealed that TGF-β signaling of immune/inflammatory regulation may play an important role in distant metastatic invasion of triple-negative breast cancer. Gene expression data and recurrence information of triple-negative breast cancer were collected and analyzed in this study. A novel set of 45-gene signature was found to be statistically predictive in disease recurrence of triple-negative breast cancer. The 45-gene signature, if further validated, may be a clinically useful tool in risk assessment of distant recurrence for early-stage triple-negative patients.
    PLoS ONE 01/2012; 7(9):e45831. · 3.73 Impact Factor
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    ABSTRACT: The number of current anti-cancer drugs was limited and the response rates were also not high. To "reposition" known drugs as anti-cancer drugs to increase the therapeutic efficiency, we presented a novel analysis framework to identify putative drugs for cancer. Using breast cancer as example, a "cancer - gene sets - drugs" network was constructed through two procedures. First, the "gene sets - drugs" network was built by applying the expression pattern of drugs for gene set enrichment analysis. Secondly, the breast cancer progression associated gene sets were identified by survival analysis of patient cohorts. By integrating the two results, 25 tumor progression associated gene sets and 360 putative anti-cancer drugs were identified. Our method has the ability to identify the "reposition" drugs and the potential affected mechanisms of tumor progression concurrently. It will be useful to speed up the development of anti-cancer drugs from bench to clinical application.
    Bioinformatics and Biomedicine (BIBM), 2012 IEEE International Conference on; 01/2012
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    ABSTRACT: The etiology of systemic lupus erythematosus (SLE) involves a complex interaction of genetic and environmental factors. Investigations have shown that environmentally driven epigenetic changes contribute to the etiology of SLE. Here, we hypothesize that aberrant DNA methylation may contribute to the activation of the immune machinery and trigger lupus disease activity. A whole genome methylation array was applied to investigate the DNA methylation changes between 12 pairs of active SLE patients and healthy controls. The results were further confirmed in 66 SLE patients, 102 healthy controls. The methylation statuses of the IL10 and IL1R2 genes were significantly reduced in the SLE patient samples relative to the healthy controls (age-adjusted odds ratios, 64.2 and 16.9, respectively, P<0.0001). There was a trend toward SLE patients having hypomethylated IL10 and IL1R2 genes accompanied by greater disease activity. We observed that the methylation degree of IL10 and IL1R2 genes were reduced in the rheumatoid arthritis (RA) patients as well but the hypomethylation change was more significant in IL1R2 genes than in the IL10 genes in RA patients. This study demonstrated that DNA hypomethylation might be associated with SLE. Hypomethylated IL10 and IL1R2 genes may provide potential epigenetic markers as clinical predictors for autoimmune diseases.
    Genes and immunity 11/2011; 13(3):214-20. · 4.22 Impact Factor
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    ABSTRACT: We performed in vivo THz transmission imaging study on a subcutaneous xenograft mouse model for early human breast cancer detection. With a THz-fiber-scanning transmission imaging system, we continuously monitored the growth of human breast cancer in mice. Our in vivo study not only indicates that THz transmission imaging can distinguish cancer from the surrounding fatty tissue, but also with a high sensitivity. Our in vivo study on the subcutaneous xenograft mouse model will encourage broad and further investigations for future early cancer screening by using THz imaging system.
    Optics Express 10/2011; 19(22):21552-62. · 3.55 Impact Factor

Publication Stats

715 Citations
282 Downloads
270.19 Total Impact Points

Institutions

  • 2013
    • University of Texas at San Antonio
      • Department of Electrical and Computer Engineering
      San Antonio, TX, United States
    • Fu Jen Catholic University
      • School of Medicine
      T’ai-pei, Taipei, Taiwan
  • 2011–2013
    • Providence University
      臺中市, Taiwan, Taiwan
  • 2008–2013
    • National Taiwan University
      • • Graduate Institute of Physiology
      • • Center for Yong Lin Biomedical Engineering
      • • Research Center for Plant Medicine
      • • Graduate Institute of Biomedical Electronics and Bioinformatic
      • • Department of Electrical Engineering
      Taipei, Taipei, Taiwan
  • 2003–2008
    • National Institutes of Health
      • • Center for Cancer Research
      • • Branch of Radiation Oncology
      • • Branch of Radiation Biology
      Bethesda, MD, United States
  • 2006–2007
    • National Cancer Institute (USA)
      • • Center for Cancer Research
      • • Radiation Biology Branch
      Bethesda, MD, United States