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Research ArticleSystematic Investigation of ScutellariaeBarbatae Herba for Treating Hepatocellular CarcinomaBased on Network Pharmacology
Benjiao Gong ,1 Yanlei Kao ,2 Chenglin Zhang,1 Fudong Sun,1 and Huishan Zhao 1
1Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China2Yantai Hospital of Traditional Chinese Medicine, Yantai, China
Correspondence should be addressed to Benjiao Gong; [email protected] and Huishan Zhao; [email protected]
Benjiao Gong and Yanlei Kao contributed equally to this work.
Received 13 June 2018; Revised 30 October 2018; Accepted 8 November 2018; Published 21 November 2018
Academic Editor: Kuzhuvelil B. Harikumar
Copyright © 2018 Benjiao Gong et al. This 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.
As the fifthmost common type ofmalignant cancers globally, hepatocellular carcinoma (HCC) is the second leading cause of cancer-related mortality worldwide. As a long-time medicinal herb in Traditional Chinese Medicine (TCM), Scutellariae Barbatae Herba(SBH) has also been used for treating various cancers including HCC, but its underlying mechanisms have not been completelyclarified. Presently, an innovative network-pharmacology platform was introduced to systematically elucidate the pharmacologicalmechanisms of SBH against HCC, adopting active ingredients prescreening, target fishing, and network analysis. The resultsrevealed that SBHappeared towork onHCCprobably through regulating 4molecular functions, 20 biological processes, and hittingon 21 candidate targets involved in 40 pathways. By in-depth analysis of the first-ranked signaling pathway and hit genes, only TTRwas highly and specially expressed in the liver tissue. TTR might play a crucial role in neutrophil degranulation pathway duringSBH against HCC. Hence, TTR might become a therapeutic target of HCC.The study investigated the anti-hepatomamechanismsof SBH from a holistic perspective, which provided a theoretical foundation for further experimental research and rational clinicalapplication of SBH.
1. Introduction
Hepatocellular carcinoma (HCC) is the fifth most commontype of malignant cancer globally and the second leadingcause of cancer-related mortality worldwide [1]. The mor-bidity of HCC is increasing and more than 50% of newcases are diagnosed in China each year [2, 3], while themedian survival of patients with advanced HCC is less than5 months [4, 5]. The high morbidity and mortality wereattributed to diagnosis executed at an advanced stage [6].The five-year survival rate is still less than 30% amongpatients subjected to hepatectomy [7]. Surgical resection,transarterial chemoembolization (TACE), tumor ablation,and liver transplantation are current treatment modalitiesand Sorafenib is the only drug approved by FDA [8, 9].Unfortunately, only TACE and the drug Sorafenib have been
shown to provide a survival benefit for patients with advancedHCC (stage II-III) [10, 11].
Scutellariae Barbatae Herba (SBH) is originated fromthe dried entire plant of Scutellaria Barbata D. Don in theLabiatae family [12], which is natively distributed throughoutKorea and southern China [13]. The herb is well renownedin Traditional Chinese Medicine (TCM) as Ban-Zhi-Lianand has been used for hundreds of years in Asian countries.Conducted by TCM theory, SBH possesses effects of heat-clearing, detoxifying, removing blood stasis, and diureticswelling and has been utilized for treating boils, swollenpoison, sore throat, and venomous snake bites for thousandsof years in China [14]. Moreover, SBH has also been usedfor treating primary liver cancer, lung cancer, and carci-noma of uterine cervix, and it is also indicated for moretypes of cancers in combination with other Chinese herbal
HindawiEvidence-Based Complementary and Alternative MedicineVolume 2018, Article ID 4365739, 12 pageshttps://doi.org/10.1155/2018/4365739
2 Evidence-Based Complementary and Alternative Medicine
medicines [15, 16]. Modern pharmacological studies haveilluminated that SBH possesses antioxidant [13], anticancer[17], antiangiogenesis, etc. activities [18]. More importantly,studies demonstrated that SBH presents effect-enhancingand toxicity-reducing actions for chemotherapy inHepatomaH22 tumor-bearing mice and a protective effect against liverdamage induced by various hepatotoxins [16, 19].Therefore, itis worthwhile to elucidate the potential mechanisms of anti-hepatoma effect.
TCM has the characteristics of multiple components,multiple targets, and synergistic effects [20], which lead tosome problems such as unclear mechanisms of action andunclear substance bases. Thereby, it is comparatively difficultto detect the accurate mechanisms of TCM through conven-tional experimental methods systematically and comprehen-sively [21]. It is necessary to illuminate scientific bases andpotential mechanisms of TCM exploring new approaches.Network pharmacology, first proposed by Andrew L Hop-kins, is a systematic analytical way based on the interactionnetwork of diseases, genes, protein targets, and drugs [22],which has substantially promoted the mechanistic studies ofherbal medicines [23, 24]. Network pharmacology (some-times also called systems pharmacology) integrates systemsbiology, omics, and computational biology to reveal themechanism of drug action from the overall perspective,which possesses integrity, synergy, and dynamic characteris-tics [25].The characteristics coincidewith those of the holistictheory of TCM.Thus,we employed network pharmacology todissect the anti-hepatoma of SBH.
In this study, we recruited active ingredients of SBHbased on Oral Bioavailability (OB) and Drug-Likeness (DL)and predicted respective targets using pharmacophore map-ping approach. HCC significant targets were retrieved fromtwo public databases and mapped to predicted targets ofactive ingredients for SBH to get common targets. Thecommon targets were executed GO and pathway analysis,which revealed the major biological processes and molecularfunctions and involved pathways during SBH against HCC.Then, the interaction networks were visualized via Cytoscapesoftware, containing the network between common targetsand associated interacting proteins and networks amongactive ingredients, common targets, and pathways.Thework-flow of the study on SBH against HCC based on networkpharmacology was shown in Figure 1.
2. Materials and Methods
2.1. Active Ingredients in SBH. The chemical ingredients wereobtained from the Traditional Chinese Medicine SystemsPharmacology Database [26] (TCMSP, http://ibts.hkbu.edu.hk/LSP/tcmsp.php), which provides an analysis platform forstudying TCM comprehensively.The active ingredients of OB≥ 30% and DL ≥ 0.18 were selected for subsequent researchreferring to the most common criteria by TCMSP database.Eventually, 29 active herbal ingredients were selected for SBH(Table S1).
2.2. Drug Targets for SBH. The PubChem database [27](https://pubchem.ncbi.nlm.nih.gov/) is a key chemical infor-mation resource, which contains the largest collection ofpublicly available chemical information. The active ingre-dients were imported into PubChem database and the 3Dmolecular structures were exported in the form of SDF fileswith the exception of 6 compounds without relevant 3Dmolecular structure information in SBH. The targets cannotbe successfully predicted in compounds lacking precise struc-tural information, which were removed. Finally, 23 herbalingredients with 3D molecular structure information wererecruited for further research. PharmMapper Server [28](http://lilab.ecust.edu.cn/pharmmapper/) is a freely accesseddatabase designed to identify potential target candidatesfor the given probe small molecules using pharmacophoremapping approach. The predicted drug targets of 23 herbalingredients were obtained from PharmMapper database. Thetargets with normalized fit score > 0.9 were harvested aspotential targets for SBH after discarding duplicate data(Table S2).
2.3. HCC Significant Targets. HCC significant targets wereretrieved from OncoDB.HCC [29] (http://oncodb.hcc.ibms.sinica.edu.tw/) and Liverome [30] (http://liverome.kobic.re.kr/index.php). OncoDB.HCC effectively integrates threedatasets from public references to provide multidimensionview of current HCC studies, as the first comprehensiveoncogenomic database for HCC. Significant genes experi-mentally validated were selected [23]. Liverome is a curateddatabase of liver cancer-related gene signatures, in whichthe gene signatures were obtained mostly from publishedmicroarray, proteomic studies and thoroughly curated byexperts. Genes of occurrence frequency > 7 among variousgene signatures were elected in Liverome [23].The duplicatedgenes were removed from two databases and the correspond-ing targets were retained (Table S3). The predicted targets ofmain active ingredients of SBH were mapped to these targetsto get common targets, which were regarded as candidatetargets of SBH (Table S4).
2.4. Protein-Protein Interaction Data. Theassociated proteinsof candidate targets of SBH were acquired from String [31](https://string-db.org, ver 10.5), with the organism limitedto “Homo sapiens”. String integrates known and forecastedprotein-protein interactions and evaluates PPI with confi-dence score ranges (low confidence: score< 0.4;medium: 0.4-0.7; high: > 0.7). PPIs with high confidence scores were keptfor further study.
2.5. Gene Ontology and Pathway Analysis. TheGO biologicalprocess and molecular function were dissected via BINGOplug-in of Cytoscape. During this procedure, the significancelevel was set to 0.01, and organism was selected as Homosapiens. The pathway analysis was executed by means ofReactome FI plug-in of Cytoscape.
2.6. Network Construction. The interaction networks wereestablished as follows: (1) network between active ingredi-ents and candidate targets of SBH; (2) network between
Evidence-Based Complementary and Alternative Medicine 3
Scutellariae Barbatae Herba
Active Ingredients in SBH
Drug Targets for SBH
Database of HCC
HCC Significant Targets
Common Targets
Ingredient - Target Network PPI Network
Molecular Function Biological ProcessPathway Analysis
Target - Pathway Network Ingredient - Target - Pathway Network
LGMN
CUBN
GC
CYP2R1LRP2
GSR
SLC4A2
SLC4A4CA2
SLC9A1
SLC25A18VDRHP
GSTO1
PTH
ST6GALNAC1
AKR1C1
DHRS9
AKR1C2
DHDH
KRT83
PCMT1SRD5A1
AKR1C3
AKR1C4
MIF
C11orf54
HGF
APOH
PRDM10
APOA1
CALM2
CALM3
CALM1
ALB
DNAH8
PQBP1
NDUFA7
SRPRB
HBD
HRSP12
RBMS1MRPL53
MBOAT4
SUGP1SCO2
MRI1
APRTGMPS
SRM
ADANCOR1
SNX12
SNX3PPIL3
MTAP
NCOA3
AURKA
MAD2L1BIRC5
BUB1UBE2C
PTTG1
TPX2DLGAP5 CENPA
CDK2
CDC6 CDK1
CCNB2
CDKN1B
CCNA2
CCNB1
CDT1
CDC20
PKMYT1
RBM12
CA1
EPB42
MYB
AHSP
ALAS2
FAM49B
SLC4A1GYPB
PTGES3SUGT1
SUGT1P3DNAJC5
DNAJB6HSP90AA1
STIP1BAG2
HSPA8
GAK
HSP90AB1BAG5
DNAJB1
DNAJC6
DNAJC3
AHSA1TTC12
TTC28
CDC37
TTC31HSPA4
RBP4
UGT1A6
CES5A GUSB
CES2
CES3
CYP3A4
CES1
UGT1A1LRAT
CDA
HNF4A
APCS
TTR
RBP1
HSPG2APP
STRA6
FOXA3
CEBPB
KLK3AR
TMPRSS2
FOXA1
NKX3-1
AKT1
IGF1RNCOA1
SRCESR1
CCND1
NCOA2
NRIP1
HRAS
BCAR1
PTPN1
GRB2
PXNCDC42
CRK
CTTN
SHC1PIK3CA
PIN1
PTPRRMAPK1
PTPN7 BSG
PEA15
MKNK1
STAT3JUN
EGFR
CBLEGF
KRAS
TP53PTPN11
EPHX1
GSTT2BGSTT1
GSTP1
CYP1A1
CYP2B6
CYP1B1
CYP1A2NFATC2
PPIA
PPP3CB
PPP3CA
NFATC3
NFATC1
PPP3R1 BUD31
VTN
CYP2E1
PLAU
SERPINE2
PRDX6
PLAUR
SERPINB2
VLDLR
AHSG
KNG1PLG
IGF1
VEGFA
SERPINE1DUSP6
FOS TGFA
MMP9
DUSP1ATF2
SRC
CCNA2
PLAU
EGFR
TTR
AURKAHRSP12
MTAP
HSPA8
Rhamnazin
CLR
5490127GSTP1GC
Baicalin
quercetin
sitosterol
rivularin
MAPK1
ALB
Stigmasterol
beta-sitosterol
667495
5484202
AKR1C2
HSP90AA1
188308
luteolin
CA25354503PPIA
26213330
baicalein
ESR1
wogonin
AR
Moslosooflavone
SalvigeninDinatin
14825644
eriodictyol
14353376
CES1
CA1
catalytic activity
carbonate dehydratase activity
nitric-oxide synthase regulator activity
enzyme regulator activity
carbon-oxygen lyase activity
molecular_function
lyase activity
lipid binding
binding
hydro-lyase activity
steroid binding
epithelium development morphogenesis of an epithelial fold
morphogenesis of an epitheliummammary gland duct morphogenesis
epithelial tube morphogenesis
tissue morphogenesis
maternal process involved in female pregnancy
reproductive process in a multicellular organism
mammary gland branching involved in pregnancy
interspecies interaction between organisms
morphogenesis of a branching epithelium
branching involved in mammary gland duct morphogenesis
morphogenesis of a branching structure
female pregnancy
tube morphogenesis
branching morphogenesis of a tubetube development
anatomical structure morphogenesis
organ morphogenesis
tissue development
mammary gland epithelium development
gland morphogenesis
reproductive structure development
mammary gland morphogenesis
developmental process
reproductive developmental process
mammary gland development
anatomical structure development
mentmulticellular organismal development
organ development
system development
developmental growth
growth
prostate gland growth
biological regulation
prostate gland development
mammary gland alveolus development
urogenital system development
mmargland development
regulation of homeostatic process
regulation of tissue remodeling
regulation of bone resorption
regulation of multicellular organismal process
regulation of bone remodeling
regulation of biological process
response to organic substance
response to steroid hormone stimulus
response to stimulus
response to hormone stimulus
response to chemical stimulus
response to estradiol stimulus
response to estrogen stimulus
response to endogenous stimulus
biological_process
multicellular organismal process
reproduction
multicellular organism reproduction
reproductive process
multi-organism process
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eriodictyol
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quercetin
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beta-sitosterol
CLR14825644
5490127Baicalin
rivularin
baicalein
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5354503
Stigmasterol
wogonin
Dinatin
5484202
188308Salvigenin
CA1
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ESR1
CES1AR
HRSP12
TTR
PLAU
HSP90AA1
SRCHSPA8
AURKA
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R-HSA-3371571R-HSA-437239
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R-HSA-194138
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GC
EGFR
CA2
AKR1C2
GSTP1
MTAP
CCNA2
MAPK1
Figure 1: Workflow for SBH against HCC.
4 Evidence-Based Complementary and Alternative Medicine
188308AR
ESR1baicalein
PPIA
26213330
5354503AKR1C2
5484202
GC
CLR
CA2
5490127
luteolin
Rhamnazin
HSP90AA1
quercetinGSTP1
eriodictyol
rivularin
Dinatin
CA1
CES1
Moslosooflavone
667495
wogonin
14825644
Salvigenin
14353376
sitosterol
Stigmasterol
MAPK1
beta-sitosterolALB
AURKAHSPA8
PLAU
SRC
EGFR
MTAP
CCNA2
TTR
HRSP12
Baicalin
Figure 2: Ingredient-target network. Green arrows represent active ingredients in SBH. Red circles represent common targets betweeningredient targets from SBH and HCC significant targets. Edges represent interaction between ingredients and targets.
common targets and associated human proteins that directlyor indirectly interacted with candidate targets of SBH; (3)network among active ingredients, common targets, andpathways. The network construction was performed viautilizing visualization software Cytoscape [32] (version 3.2.1).
3. Results and Discussion
3.1. Ingredient - Target Network Analysis. As shown in Fig-ure 2, the ingredient-target network was composed of 44nodes (23 active ingredient nodes and 21 candidate targetnodes) and 78 edges. In the network, a total of 23 activeingredients from Scutellariae Barbatae Herba were derived
from TCMSP database, which was correspondent with thecharacteristic of multiple components for TCM. Most ingre-dient nodes were connected with multiple target nodes suchas Baicalin, Dinatin, Sitosteryl acetate, etc., which coincidedwith the characteristic of multiple targets for TCM. We alsofound that many targets were hit by multiple ingredients. Forexample, ESR1 was modulated by ten ingredients containingChrysin-5-methylether, Baicalin, Sitosteryl acetate, Dinatin,baicalein, Salvigenin, Rhamnazin, and so on. CES1 wasregulated by multiple components covering 5-hydroxy-7,8-dimethoxy-2-(4-methoxyphenyl)chromone, 7-hydroxy-5,8-dimethoxy-2-phenyl-chromone, rivularin, and wogonin. Thephenomenon implied that active ingredients of SBH might
Evidence-Based Complementary and Alternative Medicine 5
LGMN
CUBN
GC
CYP2R1LRP2
GSR
SLC4A2
SLC4A4CA2
SLC9A1
SLC25A18
VDRHP
GSTO1
PTH
ST6GALNAC1
AKR1C1
DHRS9
AKR1C2
DHDH
KRT83
PCMT1SRD5A1
AKR1C3
AKR1C4
MIF
C11orf54
HGF
APOH
PRDM10
APOA1
CALM2
CALM3
CALM1
ALB
DNAH8
PQBP1
NDUFA7
SRPRB
HBD
HRSP12
RBMS1MRPL53
MBOAT4
SUGP1SCO2
MRI1
APRTGMPS
SRM
ADA
NCOR1
SNX12
SNX3PPIL3
MTAP
NCOA3
AURKA
MAD2L1BIRC5
BUB1UBE2C
PTTG1
TPX2DLGAP5 CENPA
CDK2
CDC6 CDK1
CCNB2
CDKN1B
CCNA2
CCNB1
CDT1
CDC20
PKMYT1
RBM12
CA1
EPB42
MYB
AHSP
ALAS2
FAM49B
SLC4A1GYPB
PTGES3SUGT1
SUGT1P3DNAJC5
DNAJB6
HSP90AA1
STIP1BAG2
HSPA8
GAK
HSP90AB1BAG5
DNAJB1
DNAJC6
DNAJC3
AHSA1TTC12
TTC28
CDC37
TTC31HSPA4
RBP4
UGT1A6
CES5A GUSB
CES2
CES3
CYP3A4
CES1
UGT1A1LRAT
CDA
HNF4A
APCS
TTR
RBP1
HSPG2
APP
STRA6
FOXA3
CEBPB
KLK3AR
TMPRSS2
FOXA1
NKX3-1
AKT1
IGF1RNCOA1
SRCESR1
CCND1
NCOA2
NRIP1
HRAS
BCAR1
PTPN1
GRB2
PXN
CDC42
CRK
CTTN
SHC1PIK3CA
PIN1
PTPRRMAPK1
PTPN7BSG
PEA15
MKNK1
STAT3JUN
EGFR
CBLEGF
KRAS
TP53PTPN11
EPHX1
GSTT2B
GSTT1
GSTP1
CYP1A1
CYP2B6
CYP1B1
CYP1A2NFATC2
PPIA
PPP3CB
PPP3CA
NFATC3
NFATC1
PPP3R1BUD31
VTN
CYP2E1
PLAU
SERPINE2
PRDX6
PLAUR
SERPINB2
VLDLR
AHSG
KNG1PLG
IGF1
VEGFA
SERPINE1DUSP6
FOS TGFA
MMP9
DUSP1ATF2
Figure 3: HCC targets’ PPI network. Purple Diamonds represent associated human proteins that directly or indirectly interacted withcommon targets. Red circles represent common targets between ingredient targets from SBH and HCC significant targets.
act on these targets synergistically. The network target nodesrepresented common targets from intersections betweeningredient targets from SBH and HCC significant targets,and so Figure 2 not only displayed the relationship betweenactive ingredients and ingredient targets but also reflected theconnection for SBH resisting HCC.
PharmMapper has been widely applied for computa-tional target identification and can provide the top 300
candidate targets for the query compound by default [33].The targets with normalized fit score > 0.9 were employedas potential targets in this study. Several potential targetsof active ingredients from SBH have been recognized inother studies. For example, baicalein was an indirect CARactivator and interfered with epidermal growth factor recep-tor (EGFR) signaling [34]. Wedelolactone, apigenin, andluteolin fromWedelia chinensis synergistically disrupted the
6 Evidence-Based Complementary and Alternative Medicine
catalytic activitycarbonate dehydratase activity
nitric-oxide synthase regulator activity
enzyme regulator activity
carbon-oxygen lyase activity
molecular_function
lyase activitylipid binding
binding
hydro-lyase activity
steroid binding
Figure 4: Gene Ontology (GO) Molecular FunctionAnalysis for candidate targets of SBH.The yellow nodes indicate significant enrichmentof molecular function terms. The larger the yellow node, the more the term enrichment. The darker the color, the smaller the P value (p <0.01).
AR, HER2/3, and AKT signaling networks and enhancedthe therapeutic efficacy of androgen ablation in prostatecancer [35]. Luteolin was observed to decrease sorbitolaccumulation in the rat lens under high-sorbitol conditionsex vivo via high inhibitory activity against AR and may beused as natural drugs for treating diabetic complications[36]. Luteolin was also identified as the small-moleculedrug during identifying the differentially expressed genesincluding ESR1 in kidneys undergoing laparoscopic donornephrectomy [37]. The protein expression of GSTP1 wasmainly dominated by AhR pathway and luteolin inhibitedthe expression of drug-metabolizing enzymes by modulatingNrf2 and AhR pathways [38]. Quercetin downregulated theexpression of EGFR and modulated this signal pathway onthe liver-induced preneoplastic lesions in rats [39]. On theother hand, quercetin was considered an effective anti-canceragent against breast cancer, human head and neck squamouscarcinoma, prostate cancer, oral cancer, and pancreatic tumor[40–44]. The above literature data indicated the accuracy oftarget prediction with PharmMapper.
3.2. HCC Targets’ PPI Network Analysis. The PPI networkwas composed of candidate targets of SBH and associatedhuman proteins that directly or indirectly interacted withthose in Figure 3. The network was composed of 200 nodes(21 candidate target nodes and 179 associated target nodes)and 622 edges. The network systematically and thoroughlysummarized internal net of SBH response to HCC.Themainsection of the network covered 13 (61.9%) candidate targetnodes and 107 (59.8%) associated target nodes, which might
play the leading role in the process of pharmacological effectsfor SBH.
3.3. GO and Reactome Analysis. To further excavate thesignificance of common targets, the GO molecular functionand biological process were analysed via BINGO plug-inof Cytoscape. As shown in Figure 4 and Table S5, SBHeffected HCC by regulating four principal molecular func-tions, namely, steroid binding, nitric-oxide synthase regulatoractivity, carbonate dehydratase activity, and lipid binding. Asshown in Figure 5 and Table S6, SBH mainly participatedin 20 biological processes containing response to organicsubstance, response to chemical stimulus, response to estro-gen stimulus, multi-organism process, response to steroidhormone stimulus, and so on. The yellow nodes indicatedsignificant enrichment of GO terms. The larger the yellownode, the more the term enrichment. The darker the color,the smaller the P value.
The pathway analysis was executed bymeans of ReactomeFI plug-in of Cytoscape. As shown in Table S7, the 21common targets were involved in 40 Reactome pathways( p < 0.01). It was found that SBH fought against HCCmainly depending on neutrophil degranulation, L1CAMinteractions, signaling by ERBB2, attenuation phase, TFAP2(AP-2) family regulating transcription of growth factors andtheir receptors, innate immune system, etc. Then the rele-vant target-pathway network and ingredient-target-pathwaynetwork were constructed with nodes consistent with ingre-dients, targets, pathways, and edges indicating interactions,respectively, in Figures 6 and 7. The network also indicated
Evidence-Based Complementary and Alternative Medicine 7
epithelium development morphogenesis of an epithelial fold
morphogenesis of an epitheliummammary gland duct morphogenesis
epithelial tube morphogenesis
tissue morphogenesis
maternal process involved in female pregnancy
reproductive process in a multicellular organism
mammary gland branching involved in pregnancy
interspecies interaction between organisms
morphogenesis of a branching epithelium
branching involved in mammary gland duct morphogenesis
morphogenesis of a branching structure
female pregnancy
tube morphogenesis
branching morphogenesis of a tubetube development
anatomical structure morphogenesis
organ morphogenesis
tissue development
mammary gland epithelium development
gland morphogenesis
reproductive structure development
mammary gland morphogenesis
developmental process
reproductive developmental process
mammary gland development
anatomical structure development
multicellular organismal development
organ development
system development
developmental growth
growth
prostate gland growth
biological regulation
prostate gland development
mammary gland alveolus development
urogenital system development
mmarygland development
regulation of homeostatic process
regulation of tissue remodeling
regulation of bone resorption
regulation of multicellular organismal process
regulation of bone remodeling
regulation of biological process
response to organic substance
response to steroid hormone stimulus
response to stimulus
response to hormone stimulus
response to chemical stimulus
response to estradiol stimulus
response to estrogen stimulus
response to endogenous stimulus
biological_process
multicellular organismal process
reproduction
multicellular organism reproduction
reproductive process
multi-organism process
Figure 5: Gene Ontology (GO) Biological Process Analysis for candidate targets of SBH.The yellow nodes indicate significant enrichment ofbiological process terms. The larger the yellow node, the more the term enrichment.The darker the color, the smaller the P value (p < 0.01).
8 Evidence-Based Complementary and Alternative Medicine
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R-HSA-8866910
R-HSA-3371568
R-HSA-1227986
R-HSA-6798695
R-HSA-3371556
HSP90AA1
R-HSA-1295596
R-HSA-168249
GSTP1
MTAP
CA2
HSPA8
R-HSA-445144R-HSA-3371571
R-HSA-456926
R-HSA-5654732
MAPK1
R-HSA-76002R-HSA-8863795
PPIA
R-HSA-437239
PLAU
TTR
R-HSA-3928663
R-HSA-180292
R-HSA-5654733
R-HSA-5654726
R-HSA-8864260
EGFR
R-HSA-5654727
SRC
R-HSA-4420097
R-HSA-422475
ALB
R-HSA-194138
ESR1
ARCCNA2
R-HSA-5654743 AURKA
R-HSA-1236394
GCR-HSA-191650
R-HSA-1237112
R-HSA-170145
R-HSA-5654741
R-HSA-453274R-HSA-69275
R-HSA-383280R-HSA-5654736
R-HSA-1475029R-HSA-2029480
R-HSA-6806667
Figure 6: Target-pathway network. Blue hexagons represent enriched Reactome pathways. Red circles represent common targets betweeningredient targets from SBH and HCC significant targets.
that SBH possessed multiple components, multiple targets,and multiple pathways against HCC.
Previous studies have reported that L1CAM interactions,signaling by ERBB2, attenuation phase, TFAP2 (AP-2) familyregulating transcription of growth factors and their receptors,and innate immune system played important roles in HCC[45–49], which was fully in support of the reliability ofnetwork analysis prediction. Performing in-depth analysis ofthe first-ranked signaling pathway, we found that neutrophildegranulation was involved in seven genes in this study,namely, HSPA8, HSP90AA1, GSTP1, TTR, PLAU, MAPK1,PPIA. The roles of these genes in HCC have also beenreported in previous literature. High GSTP1 could inhibit cellproliferation by reducing AKT phosphorylation and provide
a better prognosis in hepatocellular carcinoma [50].Thehigh-ranking gene MAPK1 was confirmed as an important targetinvolved in hepatocarcinogenesis [51]. The VEGF/VEGFR2pathwaymight be associatedwithHCC recurrence in patientsexpressing high levels of HSP90AA1/HSPA8 [52]. PPIA reg-ulated cell growth and could serve as a novel marker andtherapeutic molecular target for HCC patients [53]. SerumTTR might be useful for predicting the prognosis of HCCpatients [54]. The String database was employed to constructan interaction network of all hit genes. Interestingly, HSPA8,HSP90AA1, GSTP1, PLAU, MAPK1, and PPIA formed anetwork of interactions and TTRwas independent of the net-work in Figure 8. All hit genes were further analysed throughExpression Atlas, which provided RNA-seq of coding RNA
Evidence-Based Complementary and Alternative Medicine 9
667495
eriodictyol
sitosterol
luteolin
Moslosooflavone
26213330
quercetin
14353376
beta-sitosterol
CLR14825644
5490127Baicalin
rivularin
baicalein
Rhamnazin
5354503
Stigmasterol
wogonin
Dinatin
5484202
188308Salvigenin
CA1
PPIA
ESR1
CES1AR
HRSP12
TTR
PLAU
HSP90AA1
SRCHSPA8
AURKA
ALB
R-HSA-1475029
R-HSA-383280R-HSA-5654736
R-HSA-2029480R-HSA-6806667
R-HSA-1236394 R-HSA-453274
R-HSA-5654741
R-HSA-69275
R-HSA-5654743
R-HSA-1237112
R-HSA-445144R-HSA-456926
R-HSA-3371556
R-HSA-1295596
R-HSA-3371571R-HSA-437239
R-HSA-76002
R-HSA-8863795
R-HSA-8866910
R-HSA-168249
R-HSA-5654732
R-HSA-191650
R-HSA-3371453
R-HSA-373760
R-HSA-170145
R-HSA-191647
R-HSA-1227986
R-HSA-1251932
R-HSA-6798695
R-HSA-3371568
R-HSA-3928663
R-HSA-5654727
R-HSA-422475
R-HSA-4420097
R-HSA-180292
R-HSA-8864260
R-HSA-5654733
R-HSA-194138
R-HSA-5654726
GC
EGFR
CA2
AKR1C2
GSTP1
MTAP
CCNA2
MAPK1
Figure 7: Ingredient-target-pathway network. Green arrows represent active ingredients in SBH. Red circles represent common targetsbetween ingredient targets from SBH and HCC significant targets. Blue hexagons represent enriched Reactome pathways.
HSPA8
GSTP1
MAPK1
HSP90AA1
PLAU
PPIA
TTR
Figure 8: Interaction network of all hit genes.
from tissue samples of 122 human individuals representing32 different tissues. As shown in Figure 9 and Table S8,GSTP1, PLAU, and MAPK1 rendered lower expression, andHSPA8, HSP90AA1, and PPIA were expressed in variousorganizations without obvious differences. It was surprisingthat TTR was highly and specially expressed in the livertissue. TTR might play a crucial role in SBH against HCC.
4. Conclusion
23 of 29 active herbal ingredients were determined by OBandDL fromTCMSP database; their 3Dmolecular structureswere obtained fromPubChemdatabase and respective targetswere predicted via PharmMapper Database. HCC significanttargets were retrieved from OncoDB.HCC and Liverome,which were mapped to predicted targets of active ingredientsof SBH to get 21 common targets regarded as candidatetargets of SBH. The 21 common targets were analysed byCytoscape plug-ins. The results revealed that SBH effectedHCC by regulating four principal molecular functions and20 biological processes. The pathway analysis suggested the21 common targets were involved in 40 Reactome pathways.The first-ranked signaling pathway and hit genes were further
analysed through network related tools. We found that TTRwas highly and specially expressed in the liver tissue. TTRmight play a crucial role in neutrophil degranulation pathwayduring SBH against HCC. TTR might become a therapeutictarget of HCC and further experiments are needed to providesupport for our findings. This study provided a systematicview of anti-hepatoma mechanisms of Scutellariae BarbataeHerba from a network-based perspective.
Data Availability
The data used to support the findings of this study areavailable from Supplementary Materials.
Conflicts of Interest
The authors declare that they have no conflicts of interest.
Authors’ Contributions
BenjiaoGong andYanlei Kao contributed equally to thisworkand are jointly first authors.
10 Evidence-Based Complementary and Alternative Medicine
0 2802Expression level in TPM
TTR
HSPA8
HSP90AA1
PPIA
GSTP1
MAPK1
PLAU
zone
of s
kin
verm
iform
appe
ndix
urin
ary
blad
der
tons
ilth
yroi
d gl
and
testi
ssto
mac
hsp
leen
smoo
th m
uscle
tiss
uesm
all i
ntes
tine
skel
etal
mus
cle ti
ssue
saliv
a-se
cret
ing
glan
dre
ctum
pros
tate
gla
ndpl
acen
tapa
ncre
asov
ary
lym
ph n
ode
lung
liver
kidn
eyhe
art
gall
blad
der
fallo
pian
tube
esop
hagu
sen
dom
etriu
mdu
oden
umco
lon
cere
bral
cort
exbo
ne m
arro
wad
rena
l gla
ndad
ipos
e tiss
ue
Figure 9: Hit genes analysed by Expression Atlas. X-axis represents 32 different tissues. Y-axis represents hit genes.
Acknowledgments
This work is supported by Shandong Provincial NaturalScience Foundation, China (ZR2017PH047).
Supplementary Materials
Table S1: 29 active ingredients fromTCMSP. Table S2: ingredi-ents in SBHand corresponding targets. Table S3:HCC targets.Table S4: candidate targets of SBH. Table S5: Gene Ontology(GO) Molecular Function Analysis for candidate targets ofSBH. Table S6: Gene Ontology (GO) Biological ProcessAnalysis for candidate targets of SBH. Table S7: Reactomeanalysis for candidate targets of SBH. Table S8: hit genesanalysed by Expression Atlas. (Supplementary Materials)
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