Drug repurposing and therapeutic anti-miRNA predictions in oxLDL-induced the proliferation of vascular smooth muscle cell associated diseases Shun-Tsung Chen, Chien-Hung Huang, Victor C. Kok, Chi-Ying F Huang, Jin-Shuei Ciou, Jeffrey J. P. Tsai, Nilubon Kurubanjerdjit and Ka-Lok Ng * * Department of Bioinformatics & Medical Engineering Asia University, Taiwan
Contents 1. Introduction – human cardiovascular disease (CVD), drug repurposing, Connectivity Map (cMap), antimiR , 2. Methods - The eBayes algorithms for identifying DEGs, ClusterONE, cMap, DAVID, DrugBank, NCBI, miRTarBase and TarBase resources for identifying potential drugs and therapeutic antimiR 3. Results - supported by the literature, in-vitro IC 50 and clinical trials 4. Discussion - obtained certain successive results, there are still some deficiencies or limits 5. Conclusions - drug-finding pipeline is effective for drug repurposing and therapeutic antimiR discovery 2
Introduction Ø Cardiovascular disease (CVD) is the most important cause of morbidity and mortality worldwide. According to the World Health Organization (WHO) report, CVD affects tens of millions of human beings each year. Therefore, how to improve the diagnosis, treatment and prevention of CVD is an urgent and important issue. Ø The vessel is subjected to oxidized low-density lipoprotein (oxLDL) → initiate signaling pathways, then trigger differential gene expression, next induce vascular smooth muscle cell (VSMC) dedifferentiation → results in VSMC phenotypic transition → VSMC phenotypic transition is the major cause of ATs, restenosis and hypertension. 3
Blood artery and cellular structure VSMC 4
VSMC proliferation-associated diseases Heart and blood artery 5
Atherosclerosis (ATs) and VSMC 6
Hypothesis ~ ATs and cancer formation Ø Studies have suggested that ATs and cancer formation involve similar cellular processes: proliferation, inflammation and genomic instability. Ø Both types of diseases possess common pathways or signal transduction networks, such as PI3k/Akt, can mediate several functional and morphological alterations of VSMC after being activated to develop vascular diseases, as well as affect the growth, apoptosis and cell cycle regulation of various cell types to induce cancer progression. Ø It is also known that the MAPK pathway, involved in VSMC proliferation, hypertrophy, and migration, → The concept of similar therapeutic strategies and drugs is proposed to target both conditions via identifying potential drugs. 7
From disease to drug discovery The main objective of biomedical research is to connect human diseases with the genetic elements and identify drugs that treat them Nature Reviews Cancer 7(1), 54-60 (2007)
Traditional drug discovery process Reference : http://www.slidegeeks.com/shapes/product/business-steps-powerpoint- 9 templates-marketing-drug-discovery-process-ppt-slides
Drug repurposing Ø It is a recently developed approach that endeavors to identify new uses for existing drugs and has achieved certain successes. Ø It has the potential to accelerate the development and bring down the exploitation costs for drugs, as well as reducing side effects. Ø The drug-gene interaction database, cMap, is used to find potential drugs for treating the proliferation of VSMC associated diseases.
cMap Using Gene Expression Signatures to connect Drugs, Genes, and Diseases. Nature Reviews Cancer 7(1), 54-60 (2007) Science 313(5795), 1929-1935 (2006)
cMap (continued) Ø The cMap is a robust tool to address questions in different cells. → four cell line experiments, i.e. MCF7, PC3, HeL60 and SKMEL5 → dosage ( ~ 2 to 20 micro-molar), duration ( ~ 6 hours) Ø This diversity of cell types provides an opportunity to assess the extent to which results are context dependent. Ø Even though it is impossible to meet all conditions, results from different cell lines are in general acceptable to most of the users.
Search for the proliferation of VSMC associated diseases drugs Negative signature Disease query Normal Hypothesis If a drug signature could reverse, at least in part, the gene expression signature of disease, this drug might have the potential to inhibit disease pathways and thereby treat VSMC proliferation-associated diseases.
Central dogma of molecular biology miRNA & antimiR (suppress miRNA) 14
miRNA & antimiR Ø MiRNAs may modulate gene expression and protein synthesis through negatively regulating. → regulate many biological processes (BPs), such as cell development, differentiation, signaling, metabolism and etc. Ø MiR-21, 143/145 and 221/222 → actively involved in regulation of VSMC Ø MiR-145 has an anti-proliferative effect when over-expressed. 15
miRNA & antimiR (continued) ¡ The above results indicated miRNAs play a key role in the regulation of the VSMC phenotype transition and causing VSMC associated diseases. → as biomarkers in the proliferation of VSMC associated diseases diagnosis and prevention → development of miRNA-based therapeutic treatments, through using antimiRs to inhibit miRNA expression Ø MiRNA-based therapy (gene therapy) → FDA (the treatment of hyperlipidemia) 16
miRNA & antimiR (continued) Ø AntimiR mediated pharmacological inhibition of disease-associated miRNAs, shows great promise in the development of novel miRNA- based therapeutics. Ø three in vivo studies suggested that the inhibition of miR-33 by antimiR- 33 → raise HDL cholesterol levels → reverse cholesterol transport and regresses ATs → antimiR-based miRNA therapeutics could be a useful strategy for treating the proliferation of VSMC associated diseases 17
Microarray data analysis Ø The microarray experiment enables us to filter differentially expressed genes (DEGs) Ø Microarray data analysis resource, Bioconductor, was used to identify DEGs. Ø DEGs were divided into two groups ~ → up-regulated and down-regulated 18
The treatment concept of oxLDL-induced the proliferation of VSMC associated diseases Fig. 1. The concept of treatment for oxLDL-induced VSMC associated diseases. ‘Up’ and ‘down’ denote the up- and down-regulated DEGs, respectively. The dotted line denotes the interactive relationships among antimiR, miRNA and down-regulated DEGs. The arrows and the blunts denote activation and suppression respectively. 19
Methods - workflow of this study Drug repurposing and therapeutic anti-miRNA predictions (oxLDL- induced the proliferation of VSMC associated diseases): (1) DEGs identification, (2) ClusterONE analysis, (3) GO enrichment analysis, (4) KS -test, (5) drug repurposing and effectiveness verification (IC50), (6) drug target, miRNAs and antimiRs identification 20
MTT™ cell viability test & Clonogenic assay Ø MTT™ cell viability test To determine the effective cytotoxicity of screening drugs, MTT assay was used for cell viability and proliferation. In general, all incubated NSCLC cell lines (A549 and H460) were seeded in a 96-well microplate for up to 24 hrs dependent on the baseline growth rate. Ø Clonogenic assay We use two different high clonogenic lung cancer cell lines, A549 and H460 to perform the clonogenic assay. 21
Datasets Ø NCBI GEO microarray experiment, GSE13139 - made use of human aortic samples with gene expression measured at five different time course of 0, 2, 6, 12 and 24 hours. Ø Each time point measurement was repeated twice to examine the temporal patterns of the gene expression in response to oxLDL. 22
Identification of DEGs Ø Microarray data analysis resource, Bioconductor , was adopted in this study. Ø eBayes algorithm, an intrinsic function of the limma package, computes moderated t- statistics of differential expression by eBayes shrinkage of the standard errors towards a common value. moderated t -statistics is defined by 23
Identification of DEGs (continued) Ø eBayes is adopted for identifying top ranked DEGs. → DEGs with an adjusted p -values < 5% Ø up- and down-regulated DEGs were employed for searching anti-correlated drug-induced signatures → a drug found in the cMap may reverse the disease signature if the drug-induced gene expression profile is significantly negative correlated with the disease-induced gene expression profile. Ø up- or down-regulated DEGs whose expressions must satisfy below condition: Consecutively up- or down-regulated in the four time intervals, i.e. 0~2, 2~6, 6~12 and 12~24 hr. 24
ClusterONE analysis Ø To improve the drug prediction accuracy according to IC50 measurements. → ClusterONE, clustering with overlapping neighborhood expansion, is applied for generating clusters. Ø Protein-protein interaction (PPI) information from BioGRID, ClusterONE identify both the up- and down-regulated clusters. 25
Gene Ontology (GO) enrichment analysis Ø Functional annotation of the DEGs is given by DA VID → One can obtain the most relevant BPs and pathways terms associated with a given gene list. Ø The list of VSMC DEGs was submitted to DA VID → enriched BPs and KEGG pathways were obtained 26
Kolmogorov–Smirnov test (KS-test) Ø The KS -test seeks differences between two datasets, and it is non-parametric and distribution free. Ø It is conjectured that the set of consecutively up- and down-regulated DEGs may tend to cluster among the top-ranked DEGs. → we performed the KS -test for testing if this conjecture is significant or not. 27
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