• Genomics & Informatics
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• v.21 no.3
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• pp.38.1-38.8
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• 2023

Non-small cell lung cancer (NSCLC) is an important cause of cancer-associated deaths worldwide. Therefore, the exact molecular mechanisms of NSCLC are unidentified. The present investigation aims to identify the miRNAs with predictive value in NSCLC. The two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEmiRNA) and mRNAs (DEmRNA) were selected from the normalized data. Next, miRNA-mRNA interactions were determined. Then, co-expression network analysis was completed using the WGCNA package in R software. The co-expression network between DEmiRNAs and DEmRNAs was calculated to prioritize the miRNAs. Next, the enrichment analysis was performed for DEmiRNA and DEmRNA. Finally, the drug-gene interaction network was constructed by importing the gene list to dgidb database. A total of 3,033 differentially expressed genes and 58 DEmiRNA were recognized from two datasets. The co-expression network analysis was utilized to build a gene co- expression network. Next, four modules were selected based on the Z_summary score. In the next step, a bipartite miRNA-gene network was constructed and hub miRNAs (let-7a-2-3p, let-7d-5p, let-7b-5p, let-7a-5p, and let-7b-3p) were selected. Finally, a drug-gene network was constructed while SUNITINIB, MEDROXYPROGESTERONE ACETATE, DOFETILIDE, HALOPERIDOL, and CALCITRIOL drugs were recognized as a beneficial drug in NSCLC. The hub miRNAs and repurposed drugs may act a vital role in NSCLC progression and treatment, respectively; however, these results must validate in further clinical and experimental assessments.

• Genomics & Informatics
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• v.21 no.1
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• pp.6.1-6.8
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• 2023

Glaucoma is the second leading cause of irreversible blindness, and primary open-angle glaucoma (POAG) is the most common type. Due to inadequate diagnosis, treatment is often not administered until symptoms occur. Hence, approaches enabling earlier prediction or diagnosis of POAG are necessary. We aimed to identify novel drugs for glaucoma through bioinformatics and network analysis. Data from 36 samples, obtained from the trabecular meshwork of healthy individuals and patients with POAG, were acquired from a dataset. Next, differentially expressed genes (DEGs) were identified to construct a protein-protein interaction (PPI) network. In both stages, the genes were enriched by studying the critical biological processes and pathways related to POAG. Finally, a drug-gene network was constructed, and novel drugs for POAG treatment were proposed. Genes with p < 0.01 and |log fold change| > 0.3 (1,350 genes) were considered DEGs and utilized to construct a PPI network. Enrichment analysis yielded several key pathways that were upregulated or downregulated. For example, extracellular matrix organization, the immune system, neutrophil degranulation, and cytokine signaling were upregulated among immune pathways, while signal transduction, the immune system, extracellular matrix organization, and receptor tyrosine kinase signaling were downregulated. Finally, novel drugs including metformin hydrochloride, ixazomib citrate, and cisplatin warrant further analysis of their potential roles in POAG treatment. The candidate drugs identified in this computational analysis require in vitro and in vivo validation to confirm their effectiveness in POAG treatment. This may pave the way for understanding life-threatening disorders such as cancer.

• Journal of the Korea Society of Computer and Information
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• v.22 no.3
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• pp.131-138
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• 2017

New drug development is time-consuming and costly. Hence, it is necessary to repurpose old drugs for finding new indication. We suggest the way that repurposing old drug using massive literature data and biological network. We supposed a disease-drug relationship can be available if signal pathways of the relationship include significant genes identified in literature data. This research is composed of three steps-identifying significant gene using co-occurrence in literature; analyzing the shortest path on biological network; and scoring a relationship with comparison between the significant genes and the shortest paths. Based on literatures, we identify significant genes based on the co-occurrence frequency between a gene and disease. With the network that include weight as possibility of interaction between genes, we use shortest paths on the network as signal pathways. We perform comparing genes that identified as significant gene and included on signal pathways, calculating the scores and then identifying the candidate drugs. With this processes, we show the drugs having new possibility of drug repurposing and the use of our method as the new method of drug repurposing.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2008.04a
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• pp.77-86
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• 2008

It's been known that overexpression of the oncoprotein Her2 (eu/ErbB2), transmembrane receptor protein, occurs in human breast cancer. Her2-positive breast cancer patients who have Her2 overexpression show less therapeutic efficacy with enhanced metathesis and increased resistance to chemotherapy. So far, a humanized monoclonal antibody against Her2 protein called Herceptin is the only drug approved by Food and Drug Administration for treatment of Her2-overexpressing breast tumors. However, antibody therapy of Herceptin may not be ideal method for therapeutic intervention of Her2 protein expression. The therapeutic intervention of Her2 protein expression may be more efficiently achieved by inhibiting the expression of Her2 gene rather than by down-regulating the Her2 protein already overexpressed. Here, we found that the interaction of two proteins of ESX (an epithelial-restricted transcription factor) and DRIP130/CRSP130/Sur2 (a Ras-linked subunit of human mediator complexes) mediates the expression of Her2 gene. The association of ESX with Sur2 is mediated by a small hydrophobic face of 8-amino acid helix in ESX, suggesting that the ESX-Sur2 interaction can be a new novel target for Her2-positive cancer. The process to develop potent ESX-Sur2 interaction inhibitors targeting for Her2-positive cancer therapeutics will be discussed.

• Proceedings of the Korean Society of Applied Pharmacology
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• 2005.11a
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• pp.17-18
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• 2005

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.12
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• pp.5005-5006
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• 2015

Gastric cancer as one of the most common cancers worldwide has various genetic and environmental risk factors including Helicobacter pylori (H.pylori) infection. Recently, loss of a tumor suppressor gene named promyelocytic leukemia (PML) has been identified in gastric cancer. However, no mutation has been found in this gene in gastric cancer samples. Cag A H.pylori protein has been shown to exert post transcriptional regulation of some tumor suppressor genes. In order to assess such a mechanism for PML degradation, we performed in silico analyses to establish any interaction between PML and Cag A proteins. In silico interaction and docking studies showed that these two proteins may have stable interactions. In addition, we showed that imatinib kinase inhibitor can restore PML function by inhibition of casein kinase 2.

• Journal of Microbiology and Biotechnology
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• v.16 no.9
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• pp.1369-1376
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• 2006

Self-organized nanogels were prepared from pullulan/biotin conjugates (PU/Bio) for the development of an effective anticancer drug delivery system. The degree of biotin substitution was 11, 19, and 24 biotin groups per 100 anhydroglucose units of pullulan. The physicochemical properties of the nanogels (PU/Bio1, 2 and 3) in aqueous media were characterized by dynamic light scattering, transmission electron microscopy, and fluorescence spectroscopy. The mean diameter of all the samples was less than 300 nm with a unimodal size distribution. The critical aggregation concentrations (CACs) of the nanoparticles in distilled water were $2.8{\times}10^{-2},\;1.6{\times}10^{-2}$, and $0.7{\times}10^{-2}mg/ml$ for the PU/Bio1, 2, and 3, respectively. The aggregation behavior of the nanogels indicated that biotin can perform as a hydrophobic moiety. To observe the specific interaction with a hepatic carcinoma cell line (HepG2), the conjugates were labeled with rhodamine B isothiocyanate (RITC) and their intensities measured using a fluorescence microplate reader. The HepG2 cells treated with the fluorescence-labeled PU/Bio nanoparticles were strongly luminated compared with the control (pullulan). Confocal laser microscopy also confirmed internalization of the PU/Bio nanogels into the cancer cells. Such results demonstrated that the biotin in the conjugate acted as both a hydrophobic moiety for self-assembly and a tumor-targeting moiety for specific interaction with tumor cells. Consequently, PU/Bio nanogels would appear to be a useful drug carrier for the treatment of liver cancer.

• Biomolecules & Therapeutics
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• v.25 no.3
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• pp.288-295
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• 2017

The incidence of polypharmacy-which can result in drug-drug interactions-has increased in recent years. Drug-metabolizing enzymes and drug transporters are important polypharmacy modulators. In this study, the effects of bosentan and rifampin on the expression and activities of organic anion-transporting peptide (OATP) and cytochrome P450 (CYP450) 2C9 and CYP3A4 were investigated in vitro. HEK293 cells and primary human hepatocytes overexpressing the target genes were treated with bosentan and various concentrations of rifampin, which decreased the uptake activities of OATP transporters in a dose-dependent manner. In primary human hepatocytes, CYP2C9 and CYP3A4 gene expression and activities decreased upon treatment with $20{\mu}M$ $bosentan+200{\mu}M$ rifampin. Rifampin also reduced gene expression of OATP1B1, OATP1B3, and OATP2B1 transporter, and inhibited bosentan influx in human hepatocytes at increasing concentrations. These results confirm rifampin- and bosentan-induced interactions between OATP transporters and CYP450.

• Korean Journal of Clinical Pharmacy
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• v.16 no.2
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• pp.155-164
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• 2006

Great inter-variability in drug response and adverse drug reactions is related to inter-variability of drug bioavailability, drug interaction and patient's disease and physyological state that cause change in absorption, distribution, metabolism and excretion of drugs. However, these alone do not sufficiently predict and explain inter-variability in drug response. In recent studies, it is reported that inter-variability in drug response and adverse drug reactions may largely resulted from genetically determined differences in drug absoption, distribution, metabolism and drug target proteins. Especially, the major human drug-metabolizing enzymes such as CYP450, N-acetyl tranferase, thiopurine S-methyl transferase, glutathione S-transferase are identified as the major gene variants that cause inter-individual variability in drug's response and adverse drug reactions. These variations may have most significant implications for those drugs that have narrow therapeutic index and serious adverse drug reactions. Therefore, the genetic variation such as polymorphisms in drug metabolizing enzymes can affect the response of individuals to drugs that are used in the treatment of depression, psychosis, cancer, cardiovascular disorders, ulcer and gastrointestinal disorders, pain and epilepsy, among others. This review describes the pharmacogenomics of the drug metabolizing enzymes associated with the drug response and its clinical applications.

• Genomics & Informatics
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• v.20 no.3
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• pp.26.1-26.19
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• 2022

Diabetes and its related complications are associated with long term damage and failure of various organ systems. The microvascular complications of diabetes considered in this study are diabetic retinopathy, diabetic neuropathy, and diabetic nephropathy. The aim is to identify the weighted co-expressed and differentially expressed genes (DEGs), major pathways, and their miRNA, transcription factors (TFs) and drugs interacting in all the three conditions. The primary goal is to identify vital DEGs in all the three conditions. The overlapped five genes (AKT1, NFKB1, MAPK3, PDPK1, and TNF) from the DEGs and the co-expressed genes were defined as key genes, which differentially expressed in all the three cases. Then the protein-protein interaction network and gene set linkage analysis (GSLA) of key genes was performed. GSLA, gene ontology, and pathway enrichment analysis of the key genes elucidates nine major pathways in diabetes. Subsequently, we constructed the miRNA-gene and transcription factor-gene regulatory network of the five gene of interest in the nine major pathways were studied. hsa-mir-34a-5p, a major miRNA that interacted with all the five genes. RELA, FOXO3, PDX1, and SREBF1 were the TFs interacting with the major five gene of interest. Finally, drug-gene interaction network elucidates five potential drugs to treat the genes of interest. This research reveals biomarker genes, miRNA, TFs, and therapeutic drugs in the key signaling pathways, which may help us, understand the processes of all three secondary microvascular problems and aid in disease detection and management.