Identify potential drugs for cardiovascular diseases caused by stress-induced genes in vascular smooth muscle cells

Author:

Huang Chien-Hung1ORCID,Ciou Jin-Shuei2,Chen Shun-Tsung2,Kok Victor C.23ORCID,Chung Yi2,Tsai Jeffrey J. P.2,Kurubanjerdjit Nilubon4,Huang Chi-Ying F.5,Ng Ka-Lok26

Affiliation:

1. Department of Computer Science and Information Engineering, National Formosa University, Yun-Lin, Taiwan

2. Department of Bioinformatics and Medical Engineering, Asia University, Taichung, Taiwan

3. Division of Medical Oncology, Kuang Tien General Hospital Cancer Center, Taichung, Taiwan

4. School of Information Technology, Mae Fah Luang University, Chiang Rai, Thailand

5. Institute of Biopharmaceutical Sciences, National Yang-Ming University, Taipei, Taiwan

6. Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan

Abstract

BackgroundAbnormal proliferation of vascular smooth muscle cells (VSMC) is a major cause of cardiovascular diseases (CVDs). Many studies suggest that vascular injury triggers VSMC dedifferentiation, which results in VSMC changes from a contractile to a synthetic phenotype; however, the underlying molecular mechanisms are still unclear.MethodsIn this study, we examined how VSMC responds under mechanical stress by using time-course microarray data. A three-phase study was proposed to investigate the stress-induced differentially expressed genes (DEGs) in VSMC. First, DEGs were identified by using the moderated t-statistics test. Second, more DEGs were inferred by using the Gaussian Graphical Model (GGM). Finally, the topological parameters-based method and cluster analysis approach were employed to predict the last batch of DEGs. To identify the potential drugs for vascular diseases involve VSMC proliferation, the drug-gene interaction database, Connectivity Map (cMap) was employed. Success of the predictions were determined using in-vitro data, i.e. MTT and clonogenic assay.ResultsBased on the differential expression calculation, at least 23 DEGs were found, and the findings were qualified by previous studies on VSMC. The results of gene set enrichment analysis indicated that the most often found enriched biological processes are cell-cycle-related processes. Furthermore, more stress-induced genes, well supported by literature, were found by applying graph theory to the gene association network (GAN). Finally, we showed that by processing the cMap input queries with a cluster algorithm, we achieved a substantial increase in the number of potential drugs with experimental IC50 measurements. With this novel approach, we have not only successfully identified the DEGs, but also improved the DEGs prediction by performing the topological and cluster analysis. Moreover, the findings are remarkably validated and in line with the literature. Furthermore, the cMap and DrugBank resources were used to identify potential drugs and targeted genes for vascular diseases involve VSMC proliferation. Our findings are supported by in-vitro experimental IC50, binding activity data and clinical trials.ConclusionThis study provides a systematic strategy to discover potential drugs and target genes, by which we hope to shed light on the treatments of VSMC proliferation associated diseases.

Funder

Ministry of Science and Technology of Taiwan (MOST)

MOST

Asia University

Mae Fah Luang University

Publisher

PeerJ

Subject

General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

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