Gang-Gang Li,Zhan-Fang Xie,Yong-Jun Zhao,Wan-Gao Li,Guo-Feng Qi

1Department of Traditional Chinese Medicine, Anyang Vocational and Technical College, Anyang 475000, China; 2Department of Pharmacy, Anyang Tumor Hospital, Anyang 475000, China; 3 Basic Medical College, Hebei University of Chinese Medicine,Shijiazhuang 050091,China.

Abstract A novel computational system was used to decipher the targets and mechanisms of Chrysanthemum morifolium against hepatocellular carcinoma.The putative target profile of Chrysanthemum morifolium against hepatocellular carcinoma was identified from Traditional Chinese Medicine Systems Pharmacology and DrugBank.Next,identification of the protein-protein interaction network of Chrysanthemum morifolium against hepatocellular carcinoma targets, and the identification of differentially expressed genes in hepatocellular carcinoma, relied on data from the NCBI database.Finally, Kyoto Encyclopedia of Genes and Genomes and Gene Ontology were used to analyze the common targets.Forty-eight active compounds in Chrysanthemum morifolium were identified by Traditional Chinese Medicine Systems Pharmacology and DrugBank, and 71 differentially expressed genes were identified in the GEO database.Further, 10 core target proteins were selected, including CYP1A1, ADRB2,ADRA1B, PGR, MAOB, SLC6A4, GABRA1, MAOA, NOS3 and PTGS2.These target genes were also found to be associated with pathways involved in adrenergic receptor activity and catecholamine binding.

Key words: Chrysanthemum morifolium, Hepatocellular carcinoma, Network pharmacology, Adrenergic receptor activity,Catecholamine binding

Background

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related death worldwide [1].However, many HCC patients are diagnosed at an advanced stage of the disease, and their remains poor[2].Surgical resection continues to be the standard treatment for patients with early stage of HCC [3].Although good progress has been made in understanding the molecular mechanisms of HCC in recent years, the histopathological features that lead to the initiation and progression of HCC and their exact function remain a mystery.Therefore, exploring practical, rapid, and well-tolerated new drugs for HCC is warranted and may yield valuable insights.

Juhua (Chrysanthemum morifolium, CM) is the dry capitulum of Compositae plants, and has a sweet and bitter taste and slightly cold nature [4].CM is an oriental drug that has historically been used in Japan and China to treat ocular diseases.In Chinese folklore,CM is also used in herbal tea known as “Ju Hua”.CM contains volatile oils, flavonoids,triterpenoids,organic acids, and other chemical components [5].Recent studies indicate that the volatile oil from CM significantly inhibited the growth and proliferation of HepG-2 cells and tumor-bearing mice of S180 cells[6].Besides, CM extract can inhibit the proliferation of MHCC97H, which may be related to drug-induced apoptosis [7].The clinical application shows that Jindai powder with CM as the main drug has shown good curative effect in the treatment of HCC and other malignant tumors [8].However, the pharmacological mechanism of CM remains unknown due to difficulties inherent in the pathophysiological study of HCC and the lack of appropriate bioinformatics methods.Therefore, the pharmacological mechanism of CM in the treatment of HCC requires much further study.

Network pharmacology, as a new drug research model, establishes a drug-protein-disease network prediction model through bioinformatics analysis,predicts drug targets, and analyzes drug action mechanisms [9].In this work, we intended to use a comprehensive method to predict the targets and mechanism for CM against HCC based on network pharmacology.It will speed up the discovery of traditional Chinese medicine (TCM) and improve the existing drug discovery strategy.The flow chart of our experimental program is presented in Figure 1.

Figure 1 The flowchart of target prediction of chrysanthemum morifolium against hepatocellular carcinoma

Materials and methods

Construction of chemical composition database

We employed an integrated network pharmacology approach including Traditional Chinese Medicine Systems Pharmacology (TCMSP,http://tcmspw.com/tcmsp.php) and DrugBank(https://www.drugbank.ca) to get the known chemical compounds in CM.As a chemical oriented encyclopedia of herbal medicine, TCMSP provides accurate, detailed, and up-to-date biological or physicochemical results of drug actions [10].It is also worth noting that the active compounds of CM based on Lipinski's rule of five and oral bioavailability (OB)≥30%were filtered for further analysis.

Next, filtered active compounds of CM were converted to connect with the database UniProt(http://www.uniprot.org/) for CM targets standardization[11].Then,we constructed the network using the Cytoscape software (version 3.2.1.http://www.cytoscape.org/), an open source package project for visualization, integration, and analysis of molecular and genetic communication networks,which use a plug-in network analyzer to analyze the essential topological parameters [12].Finally, we utilize the“Network Analyzer” function analysis of the topology properties.

Prediction of therapeutic targets of HCC

We collected the targets of HCC from Genecards database (https://www.genecards.org), which is a searchable database integrating all known human genes platforms from about 125 network sources.With“hepatocellular carcinoma” as the keyword, HCC targets and CM targets (obtained from UniProt database) retrieved from Genecard database were mapped to Venny 2.1.0(http://bioinformatics.psb.ugent.be/webtools/Venn/).

Then, common targets were selected as the antidepressant targets of CM, and the graphic interaction in the network was visualized by Cytoscape.Additionally, we define the protein type as “Homo sapiens” to obtain the target interaction network map from the STRING database (https://string-db.org/)[13].

Besides, we screened the gene expression profiles from the GEO database.GSE19665(10 HCC samples,10 control samples) were returned by the platform of GPL8300.The expression profiles of different genes were analyzed in GEO2R(https://www.ncbi.nlm.nih.gov/geo/geo2r/).Only|log2(FC)| ＞1.5 and adjustedP-value ＜0.05 were considered as differentially expressed genes (DEGs).In addition,Shengxinren software(https://shengxin.ren)was utilized to draw the volcano plot and heat map of highly expressed genes in HCC.

GO and KEGG analyses of DEGs

As a widely applicable method, enriched biological terms of biological process, molecular functions and cellular components were identified withP＜0.05.Also, KEGG provides large-scale data collection of biological systems and interpretation and definition of molecular-level functions [14].We calculated and assessed the critical paths with the help of ClueGO plugin of Cytoscape to integrate the GO function and KEGG pathways.

Pathway enrichment performance

All imagined network graphs were created by Cytoscape and fused with the “merge” function to construct the network diagram of active components,anti-HCC targets,and metabolic pathway of CM.

Resutls

Active compound identification

Based on Lipinski's rule of five and OB ≥30%, 48 targets of the active components were predicted in the TCMSP databases and DrugBank.The network consists of 114 nodes and 329 edges, of which 40 nodes were higher than the average degree of nodes(Figure 2).The main ingredients of CM are flavonoids,triterpenoids and sterols,and volatile oil(Table 1).

Target prediction of CM against HCC

With“hepatocellular carcinoma”as the keyword, 7393 hepatocellular carcinoma related targets were mined in the Genecards database.Then,3702 HCC genes with a relevance score greater than 1.82 were selected.334 drug targets of CM and 3702 HCC genes were mapped in Venny 2.1.0 to obtain the common targets.Then,using the targets of CM as the nodes of the network,we discussed the relationship between them as edges and constructed the target-disease network of CM in Cytoscape (Figure 3A).The degree and betweenness centrality distribution of prediction targets of CM in the network graph are shown in Figure 3B and Figure 3C.In this study,to screen out proteins with significant interaction, we selected the minimum requirement of interaction score ≥ 0.4 in the STRING database as the primary criterion.PPI network data constructed in the STRING platform was shown in Figure 3D.Ten core target proteins were screened out, including PTGS2, NOS3, MAOA, GABRA1, SLC6A4, MAOB,PGR, ADRA1B, ADRB2 and CYP1A1 (Table 2).Furthermore, the volcano plot based on the genes after the filtering procedures showed that 31,051 genes simultaneously compared between these 10 normal samples and 10 HCC samples, a set of 1091 genes were found to be dysregulated by |log2(FC)| ＞1.5 andP-value ＜0.05 (Figure 4A).Most of the DEGs found in HCC were down-regulated, and amounted to 904 genes.Transcripts are up-regulated in liver, relative to normal samples, accounted for the remaining 187 genes.The heat map of DEGs of the 26 most up-regulated and down-regulated genes in HCC was illustrated in Figure 4B.

Figure 2 Compound-target network of Chrysanthemum morifolium.

Figure 3 Target-disease network of Chrysanthemum morifolium.

Table 1 Main active components and their parameters in chrysanthemum morifolium

Table 1 Main active components and their parameters in chrysanthemum morifolium(continued)

Figure 4 Volcano plot and heat map.

Table 2 Anti-hepatocellular carcinoma targets of chrysanthemum morifolium

GO biological process enrichment analysis

Results from GO pathway enrichment revealed 85 enriched pathways including adrenergic receptor activity, catecholamine binding, monoamine transport,icosanoid metabolic process, alcohol dehydrogenase activity, zinc-dependent, positive regulation of macroautophagy, bile acid and bile salt transport,multicellar organismal response to stress, drug metabolic process and steroid hormone receptor activity (Figure 5).It is suggested that the active components of CM may regulate the occurrence and development of HCC by intervening in the above biological processes.

KEGG pathway enrichment analysis

To accurately explain the primary therapeutic mechanism of CM, we obtained 19 KEGG pathways related to HCC prevention and treatment, such as tyrosine metabolism, cocaine addiction, serotonergic synapse, leishmaniasis, regulation of lipolysis in adipocytes and VEGF signaling pathway(Figure 6).To better distinguish the complete regulation of CM, we established the merged pathway(Figure 7).

Figure 5 GO biological process enrichment analysis

Figure 6 KEGG pathway enrichment analysis

Figure 7 Active ingredients-key anti-hepatocellular carcinoma targets-KEGG pathway network of chrysanthemum morifolium.

Discussion

HCC is one of the most common malignant tumors,which does great harm to human health [15].In Chinese medicine, the function of liver is to dredge and store blood,while HCC is deemed to be caused by“blood stasis”, which is closely related to “Qi stagnation” [16].Traditional Chinese medicine is composed of complex prescriptions, rendering it difficult to determine the nature so far and thereby limiting its widespread clinical application.In this study,we used pharmacological data from the network to identify the individual compounds in CM and their specific HCC-related targets.

After screening CM by Lipinski's rule of five and OB, 48 compounds were obtained, of which the most effective were eugenol (38 targets) and beta-chamigrene (19 targets).Eugenol (an essential oil of clove) displays antibacterial, antioxidant,anti-carcinogenic, cardiovascular-protective,anti-inflammatory, and anti-depression effects [17].Beta-chamigrene, is known for its anti-inflammatory,anti-carcinogenic, anti-pathological angiogenesis, and anti-depressive effects [18].This study further analyzed and predicted the chemical components,targets, biological functions, and signal transduction pathways of CM and explored the pharmacological mechanism of CM.

There are 43 overlapping genes in the drug target network and the HCC network, which may encompassing the key genes involved in the treatment of HCC.MAOB,MAOA,PTGS2,SLC6A4, andNOS3are shown to be the most active participants in these pathways.The proteins translated from these genes are implicated in cancer,inflammation,depression,anxiety,and Alzheimer’s disease.Monoamine oxidases exist in two subtypes, MAOA and MAOB, and are oxidized to destroy neurotransmitter monoamines in the brain[19].IncreasedMAOAandMAOBtranscripts in autopsied brain tissue from cirrhotic patients with hepatic encephalopathy [20].Besides,PTGS2has been shown to be capable of promoting HCC progression [21].A recent study found that the positive rate ofNOS3in the HCC relapse group was significantly higher than that in the non-recurrence group [22], suggesting thatNOS3can promote the formation of tumor blood vessels and increase tumor blood supply, which is conducive to the growth and metastasis of tumor cells.Therefore, it is reasonable to propose that CM can induceNOS3overexpression and inhibit the growth and metastasis of HCC.

In addition, we have deciphered the underlying mechanisms of major targets and corresponding functional compounds in CM acting on HCC.KEGG enrichment analyses suggested that HCC-related biological processes were enriched, including tyrosine metabolism, cocaine addiction, serotonergic synapse formation, leishmaniasis, regulation of lipolysis in adipocytes, and activation of the vascular endothelial growth factor (VEGF) signaling pathway.Tyrosine is mainly degraded in the liver by a series of enzymatic reactions.Abnormal expression of the tyrosine catabolic enzyme tyrosine aminotransferase has been reported in patients with HCC [23].Like other hypervascular solid tumors, angiogenesis of HCC is intricately regulated by VEGF and other related factors.Our data indicate that the beneficial effects of eugenol may be due to the enhancement of arginine and proline metabolism or VEGF signaling pathway.Unfortunately,the predicted results are not convincing enough, and experimental verification of more potential targets needs to be performed in the future.

In summary, these findings partially expound the mechanism of anti-HCC action in CM by network pharmacology.The present studies contribute to the understanding of the anti HCC pharmacological mechanism of CM.