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Research Article a Network Pharmacology-Based Study on the Anti-Lung Cancer Effect of Dipsaci Radix

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Research Article a Network Pharmacology-Based Study on the Anti-Lung Cancer Effect of Dipsaci Radix Hindawi Evidence-Based Complementary and Alternative Medicine Volume 2020, Article ID 7424061, 9 pages https://doi.org/10.1155/2020/7424061 Research Article A Network Pharmacology-Based Study on the Anti-Lung Cancer Effect of Dipsaci Radix Jiayan Wu,1,4 Shengkun Hong,2 Xiankuan Xie,3 and Wangmi Liu 3 1Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai 200032, China 2Quzhou People’s Hospital, No. 2 Zhongloudi, Quzhou 324000, China 3)e Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China 4Department of Neurology, Shanghai Tenth People’s Hospital Chongming Branch, Shanghai, China Correspondence should be addressed to Wangmi Liu; [email protected] Received 30 December 2019; Revised 31 March 2020; Accepted 8 April 2020; Published 28 April 2020 Academic Editor: Manel Santafe Copyright © 2020 Jiayan Wu et al. -is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Objective. Dipsaci Radix (DR) has been used to treat fracture and osteoporosis. Recent reports have shown that myeloid cells from bone marrow can promote the proliferation of lung cancer. However, the action and mechanism of DR has not been well defined in lung cancer. -e aim of the present study was to define molecular mechanisms of DR as a potential therapeutic approach to treat lung cancer. Methods. Active compounds of DR with oral bioavailability ≥30% and drug-likeness index ≥0.18 were obtained from the traditional Chinese medicine systems pharmacology database and analysis platform. -e potential target genes of the active compounds and bone were identified by PharmMapper and GeneCards, respectively. -e compound-target network and protein- protein interaction network were built by Cytoscape software and Search Tool for the Retrieval of Interacting Genes webserver, respectively. GO analysis and pathway enrichment analysis were performed using R software. Results. Our study demonstrated that DR had 6 active compounds, including gentisin, sitosterol, Sylvestroside III, 3,5-Di-O-caffeoylquinic acid, cauloside A, and japonine. -ere were 254 target genes related to these active compounds as well as to bone. SRC, AKT1, and GRB2 were the top 3 hub genes. Metabolisms and signaling pathways associated with these hub genes were significantly enriched. Conclusions. -is study indicated that DR could exhibit the anti-lung cancer effect by affecting multiple targets and multiple pathways. It reflects the traditional Chinese medicine characterized by multicomponents and multitargets. DR could be considered as a candidate for clinical anticancer therapy by regulating bone physiological functions. 1. Introduction with poor prognosis and high cost, which brings a heavy burden to society. Lung cancer is one of the leading causes of death among Bone marrow-derived myeloid cells are abundant in the all malignancies, especially in the elderly patients [1]. In tumor stroma of lung cancer, and they can promote cancer China, lung adenocarcinoma accounts for the most growth [5]. For example, myeloid-derived suppressor cells common type of lung cancers, followed by lung squamous (MDSCs) is important for tumor-associated immunosup- cell carcinoma [2]. So far, many treatments, including pressive function, which is related to the occurrence, me- surgery, drug, radiation, and biological therapies, have tastasis, and survival of cancer. In fact, MDSCs are a been adopted for lung cancer therapy. Among patients heterogeneous population of cells, including myeloid pro- with advanced non-small-cell lung cancer (NSCLC), genitor cells, immature granulocytes, immature macro- median overall survival has increased by only 1.5 months phages, and immature dendritic cells [6]. -ere is emerging despite the advent of such new therapies [3]. Over the year evidence that disruption of the programmed cell death of diagnosis, mean spending for lung cancer is higher protein 1 pathway with immune checkpoint inhibitors in- compared to breast and prostate [4]. -erefore, lung duces the immune escape of cancers with the backing of cancer has become a worldwide public health problem MDSCs [7, 8]. Researchers have tried other strategies to treat 2 Evidence-Based Complementary and Alternative Medicine lung cancer based on MDSCs, such as promotion of myeloid cell differentiation, inhibition of MDSCs expansion, elimi- Dipsaci radix nation of MDSCs, attenuation of MDSCs function, and so on [9]. Recently, Camilla et al. reported that lung cancer could OB + DL screening deploy osteoblastic cells in bones remotely even in the ab- in TCMSP sence of local metastasis, which supply lung cancer with neutrophils to foster cancer progression [10]. Dipsaci Radix (DR), also called Xu-Duan, is a traditional herbal medicine in China. According to the knowledge of Active compounds traditional Chinese medicine, DR can be used for treating fracture because it can increase bone density and alter bone Target genes prediction histomorphology [11]. -e application of DR in the treat- in pharmmapper server ment of osteoporosis has been advocated because DR could decrease the loss of bone mass [12]. However, clinical ap- plicability of DR in lung cancer remains to be determined. In view of the fact that both DR and lung cancer have effects on Target genes bone, DR may have a role in lung cancer treatment. Owing to this lack of related research, the aim of the present network pharmacology study was to define active com- pounds of DR, discover target genes of DR, and explore the potential mechanisms of DR in anti-lung cancer effect. -e GO analysis Network analysis KEGG analysis whole framework is shown in Figure 1. Figure 1: -e flowchart of network pharmacology-based strategy for the anti-lung cancer effect of DR. Abbreviations: TCMSP: 2. Materials and Methods traditional Chinese medicine systems pharmacology database and analysis platform; GO: Gene Ontology; KEGG: Kyoto Encyclopedia 2.1. Identification of Active Compounds. -e ingredients of of Genes and Genomes. DR were obtained from traditional Chinese medicines systems pharmacology database and analysis platform (TCMSP, http://lsp.nwu.edu.cn/tcmsp.php). Oral bioavail- which is a powerful tool to explore and construct PPI ability (OB) is an important indicator, which reflexes the network. In the present study, the PPI of the target genes was extent to which oral drugs can overcome intestinal wall screened with a minimum required interaction score >0.95 barriers to reach targets. Ingredients with lower OB may using the STRING online tool (version 11.0). Target genes show a less beneficial therapeutic effect because fewer ef- with high connectivity degrees in PPI network were rec- fective components enter the blood. -e drug-likeness (DL) ognized as hub genes. index was used to distinguish between drugs and nondrugs. Molecules with lower DL values mean that such molecules 2.4. Gene Ontology (GO) Term and Kyoto Encyclopedia of are less likely to be drugs [13]. In this study, the optimal Genes and Genomes (KEGG) Pathway Enrichment Analyses. cutoff values of OB and DL were 30% and 0.18, respectively. GO is a database for the unification of biology. It has three Ingredients of DR with values above these thresholds were categories, including biological processes, molecular func- considered as active compounds. tions, and cellular components [18]. KEGG, a knowledge database, helps researchers to classify selected gene sets into 2.2. Target Genes Prediction. -e interactions between their respective signaling pathways [19]. To explore the each active compound and its target genes were obtained potential molecular mechanisms for the anti-lung cancer from PharmMapper server (http://www.lilab-ecust.cn/ effect of DR, GO term and KEGG pathway enrichment pharmmapper/). Using pharmacophore mapping ap- analyses were performed using R software (version 3.6.1). proach, it can provide researchers with potential target P < 0:05 was set as the threshold value. candidates for the given probe small molecules [14, 15]. GeneCards, the human gene compendium, enabled us to 3. Results effectively navigate and interrelate human genes and bone. -erefore, the target genes related to the anti-lung cancer 3.1.ActiveCompoundsFiltering. Search results from TCMSP effect of DR were considered as the overlap part of the results showed that traditional ingredients of DR include 31 kinds of from the two above databases. ingredients. Among these ingredients, total of 6 active compounds in DR with OB ≥ 30% and DL ≥ 0.18 were re- trieved from TCMSP (Table 1). 2.3. Network Construction. -e complex relationships be- tween lung cancer, DR, active compounds, and target genes were visualized using Cytoscape software (version 3.7.2) 3.2. TargetGenes Prediction. 17,250 target genes which could [16]. -e Search Tool for the Retrieval of Interacting Genes correspond to bone were identified from GeneCards (STRING) database [17] is a precomputed global resource, (Table S1). Target genes with the normalized fit score were Evidence-Based Complementary and Alternative Medicine 3 Table 1: Active compounds in DR. ID Molecule name MW OB (%) DL MOL003152 Gentisin 258.24 64.06 0.21 MOL008188 Japonine 295.36 44.11 0.25 MOL009322 Sylvestroside_III 686.83 48.02 0.53 24 3,5-Di-O- MOL009312 516.49 48.14 0.68 caffeoylquinic_acid Bone 16996 254 Active compounds MOL000359 Sitosterol 414.79 36.91 0.75 MOL009317 Cauloside_A 444.72 43.32 0.81 MW, molecular weight; OB, oral bioavailability; DL, drug-likeness. selected from PharmMapper server for every active com- pound. After duplicates elimination, 278 target genes for active compounds were identified according to the Uniprot Figure 2: Venn diagram of the target genes for bone and active identifiers mapping (Table S2). -ere were 254 overlapping compounds. Bone has 17,250 target genes, while active compounds target genes between bone and active compounds (Table S3 have 278 target genes. -ere are 254 overlapping target genes and Figure 2). between the two sets. 3.3. Protein-Protein Interaction (PPI) Network.
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