Open Access
CC BY 4.0 · Chinese medicine and natural products 2022; 02(02): e77-e88
DOI: 10.1055/s-0042-1755401
Original Article

Potential Mechanisms of Yanghe Decoction in the Treatment of Soft Tissue Sarcoma and Arteriosclerosis Obliterans Based on Network Pharmacology

Yiran Zhai
1   The First Clinical Medical College, Henan University of Chinese Medicine, Zhengzhou, Henan, China
,
Shiqing Jiang
2   Department of Hematology and Oncology, The First Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, Henan, China
,
Binyi Li
1   The First Clinical Medical College, Henan University of Chinese Medicine, Zhengzhou, Henan, China
,
Lili Miao
1   The First Clinical Medical College, Henan University of Chinese Medicine, Zhengzhou, Henan, China
,
Jie Wang
1   The First Clinical Medical College, Henan University of Chinese Medicine, Zhengzhou, Henan, China
,
Shanshan Li
1   The First Clinical Medical College, Henan University of Chinese Medicine, Zhengzhou, Henan, China
› Author Affiliations

Funding This study was supported by 2018 scientific and technological research projects in Henan Province (192102310430), Special Project of Chinese Medicine Research in Henan Province (2019ZYZD06)
 

Abstract

Objective The objective of this study was to investigate potential mechanisms of Yanghe Decoction (, YHD) in treating soft tissue sarcoma (STS) and arteriosclerosis obliterans (ASO) based on the use of network pharmacology.

Methods Candidate compounds and potential targets were identified through the TCM Systems Pharmacology database and a comprehensive literature search. Related targets of STS and ASO were collected in the GeneCards database, DisGeNET database, and Drugbank database. Furthermore, The STRING 11.0 database was used to determine protein–protein interaction (PPI) networks; common targets were obtained and imported into Cytoscape 3.7.2. Then, a PPI network comprising common targets was drawn, and network topology analysis was performed to screen for key shared targets. Gene ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of key shared targets were performed by using Metascape software. Subsequently, a compound–target–pathway network was constructed via Cytoscape 3.7.2.

Results The following signaling pathways were found to be associated with the mechanisms of YHD in treating STS and ASO: AGE-RAGE signaling pathway, IL-17 signaling pathway; HIF-1 signaling pathway, TNF signaling pathway, interactions between cytokines and cytokine receptors, Th17 cell differentiation, and NOD-like receptor signaling pathway. Among the compounds and targets involved in these pathways, quercetin, luteolin, and kaempferol were found to be core compounds, and TNF, IL-6, and MAPK1 were found to be core targets.

Conclusion Taken together, our findings elucidated that potential mechanisms of YHD in treating STS and ASO involved cellular proliferation/differentiation, angiogenesis, inflammation, immune responses, oxidative stress, and other related signaling pathways.


Introduction

Soft tissue sarcoma (STS) is a malignant solid tumor derived from fat, fascia, muscle, fibers, lymph, and blood vessels. The incidence rate of STS in China is approximately 2.38/100,000 individuals per year, and this rate continues to increase.[1] Arteriosclerosis obliterans (ASO) involves chronic occlusion of peripheral arteries caused by long-term atherosclerosis, which mostly occurs in the lower extremities. The prevalence of ASO in the elderly is particularly high. Due to the increase in the proportion of the aging population in China, the incidence of ASO is also increasing each year, and it has become an urgent public health and medical problem in China.[2]

Traditional Chinese medicine (TCM) posits that STS belongs to the categories of “sarcoma” and “stone gangrene.” The occurrence of STS is related to a lack of vital qi and attack by cold pathogen, which leads to qi stagnation, blood stasis, and phlegm resistance. Yanghe Decoction (, YHD), used as a treatment in STS patients, has been shown to significantly improve clinical symptoms and extend survival time.[3] [4] ASO belongs to the category of “necrosis” in TCM and is mostly the result of yang deficiency in spleen and kidney, with coldness and wetness as external manifestations, which leads to qi and blood stagnation, and obstruction of channels. YHD has the function of warming yang and tonifying blood, dispersing cold and dredging stagnation. Therefore, it is commonly used in the treatment of ASO.[5] [6]

Although the above findings suggest that YHD may be efficacious in treating both STS and ASO, its underlying mechanisms in this therapeutic process remain unknown. Unfortunately, traditional pharmacological research methods alone are not sufficient to fully elucidate the mechanisms of action of YHD. In contrast, network pharmacology is a powerful tool for investigating the mechanisms of action of TCM compounds. In particular, network pharmacology assesses multilevel relationships of compounds, targets, and pathways to provide insights into the mechanisms of action of TCM compounds.[7] [8] In the present study, we have used network pharmacology to investigate the mechanisms of action of YHD in treating both STS and ASO, which may provide useful findings for further experimental research and clinical applications.


Materials and Methods

Screening of Chemical Components of YHD

We used the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database and analysis platform[9] and an extensive literature search to identify candidate compounds and targets of the following six key components in YHD: Shudihuang (Rehmannia glutinosa, SD), Rougui (Cinnamomum cassia Presl, RG), Mahuang (Ephedra sinica Stapf, MH), Jiezi (Semen sinapis, JZ), Sheng jiang (Zingiber officinale Rosc, SJ), and Gancao (Glycyrrhiza uralensis Fisch, GC). Lujiao Jiao (Colla Corni Cervi) was excluded since it was not suitable for our present pharmacological study. According to the absorption, distribution, metabolism, and excretion parameters in the TCMSP database, Chinese medicinal compounds with oral bioavailability ≥30% and with a drug-like-index (DL) ≥0.18 were selected as candidate compounds.


Collection and Treatment of Targets in YHD

We obtained potential targets of the candidate compounds through the TCMSP database, uploaded them into the UniProt database (https://www.uniprot.org/), limited the species to “human,” and obtained the genetic information corresponding to each protein target. Then, we imported these data into Cytoscape 3.7.2 to build a compound–target–pathway network diagram.


Acquisition of Common Targets of YHD in the Treatment of STS and ASO

We used “soft tissue sarcoma” and “arteriosclerosis obliterans” as search terms in the GeneCards database (https://www.genecards.org), DisGeNET database (https://www.disgenet.org/), and Drugbank database (https://www.drugbank.ca) to collect disease targets related to STS and ASO. If there were too many disease targets in the database, we defined targets with scores greater than the median score as potential targets. Then, we merged potential targets obtained from each database and removed any duplicates. Subsequently, we determined cross targets, and the cross targets were displayed via a Venn diagram through OmicShare (https://omicshare.com/index.php).


Screening of Key Shared Targets

We entered the obtained common targets into the STRING 11.0 database (https://string-db.org/). The organism category was set to Homo sapiens. We obtained protein–protein interaction networks of the common targets via a combined score >0.4 as the screening criterion. Then, we imported the screened information into Cytoscape 3.7.2 to plot the protein–protein interaction network between the common targets and performed network topology analysis. Key shared targets were selected according to values greater than the median.


GO Function Enrichment and KEGG Signal Pathway Enrichment Analysis

We uploaded the key common targets to Metascape (https://metascape.org/) and set the parameter to H species to obtain the gene ontology (GO) function enrichment analysis results and Kyoto Encyclopedia of Genes and Genomes (KEGG) signal pathway enrichment analysis results. GO functional enrichment analysis includes biological process (BP), cell composition (CC), and molecular function (MF). According to the value of log (10)p, we used the bioinformatics online mapping tool to visualize various top-ranked GO items and filtered out the top 20 signaling pathways according to theirs. OmicShare was used to visualize the results of enrichment analysis of the top 20 KEGG pathways. Finally, we imported these data into Cytoscape 3.7.2 to construct a compound–target–pathway interaction network.



Results

Screening of Chemical Components of YHD

We identified a total of 76 chemical constituents of SD, 103 chemical constituents of RG, 363 chemical constituents of MH, 37 chemical constituents of JZ, 265 chemical constituents of SJ, and 280 chemical constituents of GC. A total of 129 candidate chemical constituents were obtained after screening, including two chemical constituents of SD, three chemical constituents of RG, 23 chemical constituents of MH, three chemical constituents of JZ, five chemical constituents of SJ, and 92 chemical constituents of GC. After deleting duplicates, a total of 118 chemical components were obtained ([Table 1]).

Table 1

Basic information of 118 candidate compounds of YHD

Drud

Mol ID

Molecule Name

OB (%)

DL

SD

MOL000359

Sitosterol

36.91

0.75

MOL000449

Stigmasterol

43.83

0.76

RG

MOL000004

procyanidin B1

67.87

0.66

MOL000422

Kaempferol

41.88

0.24

MOL000098

Quercetin

46.43

0.28

MH

MOL010788

Leucopelargonidin

57.97

0.24

MOL002823

Herbacetin

36.07

0.27

MOL010489

Resivit

30.84

0.27

MOL004798

Delphinidin

40.63

0.28

MOL000006

Luteolin

36.16

0.25

MOL000492

(+)-catechin

54.83

0.24

MOL001494

Mandenol

42

0.19

MOL001506

Supraene

33.55

0.42

MOL001755

24-Ethylcholest-4-en-3-one

36.08

0.76

MOL002881

Diosmetin

31.14

0.27

MOL004328

Naringenin

59.29

0.21

MOL004576

Taxifolin

57.84

0.27

MOL005043

Campest-5-en-3β-ol

37.58

0.71

MOL005190

Eriodictyol

71.79

0.24

MOL005573

Genkwanin

37.13

0.24

MOL005842

Pectolinarigenin

41.17

0.3

MOL007214

(+)-Leucocyanidin

37.61

0.27

MOL011319

Truflex OBP

43.74

0.24

JZ

MOL010690

Uniflex BYO

30.13

0.25

MOL013037

2-(2-phenylethyl)-6-[[(5S,6R,7R,8S)-5,6,7-trihydroxy-4-keto-2-(2-phenylethyl)-5,6,7,8-tetrahydrochromen-8-yl]oxy]chromone

31.31

0.61

MOL001697

Sinoacutine

63.39

0.53

SJ

MOL000358

β-sitosterol

36.91

0.75

MOL006129

6-methylgingediacetate2

48.73

0.32

MOL001771

Poriferast-5-en-3β-ol

36.91

0.75

MOL008698

Dihydrocapsaicin

47.07

0.19

GC

MOL001484

Inermine

75.18

0.54

MOL001792

DFV

32.76

0.18

MOL000211

Mairin

55.38

0.78

MOL002311

Glycyrol

90.78

0.67

MOL000239

Jaranol

50.83

0.29

MOL002565

Medicarpin

49.22

0.34

MOL000354

Isorhamnetin

49.6

0.31

MOL003656

Lupiwighteone

51.64

0.37

MOL003896

7-Methoxy-2-methyl isoflavone

42.56

0.2

MOL000392

Formononetin

69.67

0.21

MOL000417

Calycosin

47.75

0.24

MOL004805

(2S)-2-[4-hydroxy-3-(3-methylbut-2-enyl) phenyl]-8,8-dimethyl-2,3-dihydropyrano [2,3-f]chromen -4-one

31.79

0.72

MOL004806

Euchrenone

30.29

0.57

MOL004808

Glyasperin B

65.22

0.44

MOL004810

Glyasperin F

75.84

0.54

MOL004811

Glyasperin C

45.56

0.4

MOL004814

Isotrifoliol

31.94

0.42

MOL004815

(E)-1-(2,4-dihydroxyphenyl)-3-(2,2-dimethylchromen-6-yl) prop-2-en-1-one

39.62

0.35

MOL004820

Kanzonols W

50.48

0.52

MOL004824

(2S)-6-(2,4-dihydroxyphenyl)-2-(2-hydroxypropan-2-yl)-4-methoxy-2,3-dihydrofuro[3,2-g]chromen-7-one

60.25

0.63

MOL004827

Semilicoisoflavone B

48.78

0.55

MOL004828

Glepidotin A

44.72

0.35

MOL004829

Glepidotin B

64.46

0.34

MOL004833

Phaseolinisoflavan

32.01

0.45

MOL004835

Glypallichalcone

61.6

0.19

MOL004838

8-(6-hydroxy-2-benzofuranyl)-2,2-dimethyl-5-chromenol

58.44

0.38

MOL004841

Licochalcone B

76.76

0.19

MOL004848

Licochalcone G

49.25

0.32

MOL004849

3-(2,4-dihydroxyphenyl)-8-(1,1-dimethylprop-2-enyl)-7-hydroxy-5-methoxy-coumarin

59.62

0.43

MOL004855

Licoricone

63.58

0.47

MOL004856

Gancaonin A

51.08

0.4

MOL004857

Gancaonin B

48.79

0.45

MOL004860

Glycyrrhiza uralensis Fisch glycoside E

32.89

0.27

MOL004863

3-(3,4-dihydroxyphenyl)-5,7-dihydroxy-8-(3-methylbut-2-enyl)chromone

66.37

0.41

MOL004864

5,7-dihydroxy-3-(4-methoxyphenyl)-8-(3-methylbut-2-enyl)chromone

30.49

0.41

MOL004866

2-(3,4-dihydroxyphenyl)-5,7-dihydroxy-6-(3-methylbut-2-enyl)chromone

44.15

0.41

MOL004879

Glycyrin

52.61

0.47

MOL004882

Licocoumarone

33.21

0.36

MOL004883

Licoisoflavone

41.61

0.42

MOL004884

Licoisoflavone B

38.93

0.55

MOL004885

Licoisoflavanone

52.47

0.54

MOL004891

Shinpterocarpin

80.3

0.73

MOL004898

(E)-3-[3,4-dihydroxy-5-(3-methylbut-2-enyl)phenyl]-1-(2,4-dihydroxyphenyl)prop-2-en-1-one

46.27

0.31

MOL004903

Liquiritin

65.69

0.74

MOL004904

Licopyranocoumarin

80.36

0.65

MOL004905

3,22-Dihydroxy-11-oxo-delta(12)-oleanene-27-α-methoxycarbonyl-29-oic acid

34.32

0.55

MOL004907

Glyzaglabrin

61.07

0.35

MOL004908

Glabridin

53.25

0.47

MOL004910

Glabranin

52.9

0.31

MOL004911

Glabrene

46.27

0.44

MOL004912

Glabrone

52.51

0.5

MOL004913

1,3-dihydroxy-9-methoxy-6-benzofurano[3,2-c]chromenone

48.14

0.43

MOL004914

1,3-dihydroxy-8,9-dimethoxy-6-benzofurano[3,2-c]chromenone

62.9

0.53

MOL004915

Eurycarpin A

43.28

0.37

MOL004917

Glycyroside

37.25

0.79

MOL004924

(-)-Medicocarpin

40.99

0.95

MOL004935

Sigmoidin-B

34.88

0.41

MOL004941

(2R)-7-hydroxy-2-(4-hydroxyphenyl) chroman-4–one

71.12

0.18

MOL004945

(2S)-7-hydroxy-2-(4-hydrox yphenyl)-8-(3-methylbut-2-enyl) chroman-4-one

36.57

0.32

MOL004948

Isoglycyrol

44.7

0.84

MOL004949

Isolicoflavonol

45.17

0.42

MOL004957

HMO

38.37

0.21

MOL004959

1-Methoxyphaseollidin

69.98

0.64

MOL004961

Quercetin der

46.45

0.33

MOL004966

3′-Hydroxy-4'-O-Methylglabridin

43.71

0.57

MOL000497

Licochalcone A

40.79

0.29

MOL004974

3′-Methoxyglabridin

46.16

0.57

MOL004978

2-[(3R)-8,8-dimethyl-3,4-dihydro-2H-pyrano[6,5-f]chromen-3-yl]-5-methoxyphenol

36.21

0.52

MOL004980

Inflacoumarin A

39.71

0.33

MOL004985

Icos-5-enoic acid

30.7

0.2

MOL004988

Kanzonol F

32.47

0.89

MOL004989

6-prenylated eriodictyol

39.22

0.41

MOL004990

7,2',4'-trihydroxy-5-methoxy-3-arylcoumarin

83.71

0.27

MOL004991

7-Acetoxy-2-methylisoflavone

38.92

0.26

MOL004993

8-prenylated eriodictyol

53.79

0.4

MOL004996

Gadelaidic acid

30.7

0.2

MOL000500

Vestitol

74.66

0.21

MOL005000

Gancaonin G

60.44

0.39

MOL005001

Gancaonin H

50.1

0.78

MOL005003

Licoagrocarpin

58.81

0.58

MOL005007

Glyasperins M

72.67

0.59

MOL005008

Glycyrrhiza flavonol A

41.28

0.6

MOL005012

Licoagroisoflavone

57.28

0.49

MOL005013

18α-hydroxyglycyrrhetic acid

41.16

0.71

MOL005016

Odoratin

49.95

0.3

MOL005017

Phaseol

78.77

0.58

MOL005018

Xambioona

54.85

0.87

MOL005020

dehydroglyasperins C

53.82

0.37

Abbreviation: DL, drug-like-index; GC, Gancao; JZ, Jiezi; MH, Mahuang; OB, oral bioavailability; RG, Rougui; SD, Shudihuang; SJ, Sheng jiang; YHD, Yanghe Decoction.



Collection and Treatment of Targets in YHD

We obtained 28 targets of SD, 153 targets of RG, 209 targets of MH, 17 targets of JZ, 49 targets of SJ, and 213 targets of GC. After deleting duplicates, a total of 233 drug targets were obtained, which were imported into Cytoscape 3.7.2 to construct a drug–compound–target interaction network ([Fig. 1]).

Zoom
Fig. 1 Network of drugs–compounds–targets related to YHD in the treatment of STS/ASO. Notes: The regulatory network was constructed by 357 nodes (six Chinese herbs, 118 candidate compound nodes, and 233 target nodes) and 1,769 edges; among the 118 candidate compounds, eight compounds had no corresponding targets found in the database; purplish-red represents Chinese herbs, blue represents compound, yellow represents target,and the size of node is directly proportional to the Degree value of node.

Acquisition of Common YHD Targets in the Treatment of STS and ASO

We obtained 1,615 STS disease targets and 223 ASO disease targets. The above two groups of disease targets were intersected with 233 compound targets in YHD ([Fig. 2]), which yielded a total of 43 common targets, as follows: MMP2, PLAU, NOS2, UGT1A1, GJA1, CRP, CXCL8, SELE, THBD, TNF, IL1A, LDLR, MPO, STAT3, SLPI, CTSD, VEGFA, TGF-1β, CCL2, MMP1, STAT1, IL-6, GSR, HMOX1, MMP3, IL-10, MAPK1, PLAT, SOD1, IL-2, IFNG, IL-4, ICAM1, HIF1A, NOS3, CXCL10, SERPINE1, VCAM1, IL-1β, PTGS1, F3, CYP3A4, and MMP9.

Zoom
Fig. 2 Venn diagram of YHD targets in the treatment of STS and ASO.

Screening and Analysis of Key Shared Targets

The interaction network between common target proteins is shown in [Fig. 3]. Through network topology analysis, 20 key common targets were screened out. The specific key common targets were as follows: TNF, IL-6, IL-1β, VEGFA, MMP9, CCL2, IL-10, CXCL8, VCAM1, ICAM1, MMP2, SERPINE1, MPO, IL-4, MAPK1, NOS3, CRP, HMOX1, STAT3, and IFNG.

Zoom
Fig. 3 Protein–protein interaction network of the common targets of YHD and STS/ASO.

GO and KEGG Analyses

A total of 745 BPs were obtained and were mainly related to cell migration, cell apoptosis, cytokine metabolism, and cell response to biological stimuli. A total of 12 CCs were obtained and involved membrane rafts, membrane microdomains, membrane domains, and the extracellular matrix. A total of 14 MFs were obtained and involved cytokine activity, receptor ligand activity, growth factor activity, and chemokine receptor binding. The top-ranked items included cytokine-mediated signaling pathways, positive regulation of cell migration, positive regulation of cell motility, positive regulation of cellular-component movement, positive regulation of locomotion, and other matters ([Fig. 4]). KEGG pathway enrichment analysis yielded 65 signaling pathways, among which the top 20 pathways included the AGE-RAGE signaling pathway (related to diabetic complications), IL-17 signaling pathway, and HIF-1 signaling pathway and other matters ([Table 2]). The results of KEGG pathway enrichment analysis of the top 20 KEGG pathways were visualized using OmicShare ([Fig. 5]) and were then imported into Cytoscape 3.7.2 to build a compound–target–pathways interaction network ([Fig. 6]).

Zoom
Fig. 4 GO enrichment analysis.
Zoom
Fig. 5 KEGG signaling pathway enrichment analysis (top 20).
Zoom
Fig. 6 Network of compoundstargetspathways related to YHD in the treatment of STS/ASO. Notes: The network consists of 56 nodes (18 compounds,18 key common targets, and 20 pathway nodes) and 203 edges; purple represents the pathway, blue represents the compound, yellow represents the target, and the size of the node is directly proportional to the degree value of the node.
Table 2

Enrichment analysis of KEGG signaling pathway (top 20)

ID

Term

p-Value

Genes

hsa04933

AGE-RAGE signaling pathway in diabetic complications

3.06987E-27

ICAM1、IL-1β、IL-6、CXCL8、MMP2、NOS3、SERPINE1、MAPK1、CCL2、STAT3、TNF、VCAM1、VEGFA

hsa05418

Fluid shear stress and atherosclerosis

3.1339E-20

HMOX1、ICAM1、IFNG、IL-1β、MMP2、MMP9、NOS3、CCL2、TNF、VCAM1、VEGFA

hsa05144

Malaria

4.40514E-20

ICAM1、IFNG、IL-1β、IL-6、CXCL8、IL-10、CCL2、TNF、VCAM1

hsa04657

IL-17 signaling pathway

2.0254E-17

IFNG、IL-1β、IL-4、IL-6、CXCL8、MMP9、MAPK1、CCL2、TNF

hsa05142

Chagas disease

(American trypanosomiasis)

4.80526E-17

IFNG、IL-1β、IL-6、CXCL8、IL-10、SERPINE1、MAPK1、CCL2、TNF

hsa05143

African trypanosomiasis

5.40725E-16

ICAM1、IFNG、IL-1β、IL-6、IL-10、TNF、VCAM1

hsa05323

Rheumatoid arthritis

3.27888E-15

ICAM1、IFNG、IL-1β、IL-6、CXCL8、CCL2、TNF、VEGFA

hsa04066

HIF-1 signaling pathway

8.507E-15

HMOX1、IFNG、IL-6、NOS3、SERPINE1、MAPK1、STAT3、VEGFA

hsa04668

TNF signaling pathway

1.47723E-14

ICAM1、IL-1β、IL-6、MMP9、MAPK1、CCL2、TNF、VCAM1

hsa05321

Inflammatory bowel disease

5.51947E-14

IFNG、IL-1β、IL-4、IL-6、IL-10、STAT3、TNF

hsa04060

Cytokine-cytokine receptor interaction

3.59495E-13

IFNG、IL-1β、IL-4、IL-6、CXCL8、IL-10、CCL2、TNF、VEGFA

hsa05164

Influenza A

6.88443E-13

ICAM1、IFNG、IL-1β、IL-6、CXCL8、MAPK1、CCL2、TNF

hsa05140

Leishmaniasis

2.31419E-11

IFNG、IL-1β、IL-4、IL-10、MAPK1、TNF

hsa05133

Pertussis

2.96757E-11

IL-1Β、IL-6、CXCL8、IL-10、MAPK1、TNF

hsa05146

Amoebiasis

1.24592E-10

IFNG、IL-1β、IL-6、CXCL8、IL-10、TNF

hsa05219

Bladder cancer

1.66454E-10

CXCL8、MMP2、MMP9、MAPK1、VEGFA

hsa04659

Th17 cell differentiation

2.41559E-10

IFNG、IL-1β、IL-4、IL-6、MAPK1、STAT3

hsa05161

Hepatitis B

1.46222E-09

IL-6、CXCL8、MMP9、MAPK1、STAT3、TNF

hsa04621

NOD-like receptor signaling pathway

3.97175E-09

IL-1β、IL-6、CXCL8、MAPK1、CCL2、TNF

hsa05152

Tuberculosis

5.41283E-09

IFNG、IL-1β、IL-6、IL-10、MAPK1、TNF

Abbreviation: KEGG, Kyoto Encyclopedia of Genes and Genomes.




Discussion

YHD is derived from the Waike Zhengzhi Quansheng Ji.[10] SD can nourish yin and blood. RG and SJ can warm the yang and dissolve the cold. MH can open the sweat pores of the skin and release pathogens. JZ can dredge collaterals and resolve phlegm. GC can nourish qi and detoxify and harmonize medicines. STS is a type of malignant solid tumor. The formation of STS is due to an imbalance of yin and yang. Yang deficiency leads to cold coagulation, phlegm obstruction, blood stasis, and eventually leads to tumors. Cold dampness pathogen is the superficial reason of ASO, while yang deficiency of spleen and kidney is the root cause. Most of the patients are middle aged and elderly people, who often have the syndromes of deficiency, blood stasis, and phlegm. It can be seen that the above two diseases have yang deficiency, phlegm dampness, and blood stasis in varying degrees. YHD can warm yang to regenerate qi and blood and remove cold to dredge collaterals and disperse accumulation. Therefore, it theoretically explains the reason why YHD can treat STS and ASO.

In the present study, we used network pharmacology to identify signaling pathways involved in the effects of YHD in treating STS and ASO, which included the following: the AGE-RAGE signaling pathway, IL-17 signaling pathway, HIF-1 signaling pathway, TNF signaling pathway, interactions of cytokines and cytokine receptors, Th17 cell differentiation, and NOD-like receptor pathway. The topological properties were analyzed based on the degree values and corresponding intermediary values in the two networks of drug–compound–targets and compound–target–pathways. The most important compounds were determined to be quercetin, luteolin, and kaempferol. Additionally, the most critical targets were found to be TNF, IL-6, and MAPK1. To corroborate these findings, we performed an extensive literature search and further explored the mechanisms of YHD in the treatment of STS and ASO.

Quercetin[11] and luteolin[12] exhibit proteasome inhibitory activity and have significant effects in overcoming multidrug resistances of various tumors such as sarcomas. Quercetin[12] and kaempferol[13] can inhibit tumor invasion and metastasis by inhibiting the activity of MMP-9 in human fibrosarcoma HT1080 cells. Quercetin can induce apoptosis of human liposarcoma SW 872 cells by down-regulating Bcl-2, cleaving PARP, and activating caspase-3, Bax, and Bak.[14] Luteolin can down-regulate β-catenin expression, inhibit Wnt signaling, and reduce the formation of fibromatosis, sarcoma, and mesenchymal tumors.[15] Quercetin,[16] luteolin,[17] and kaempferol[18] all have anticoagulant, antithrombotic, antiplatelet-aggregation, and defibrillating effects. Quercetin can also exert antiarterial effects by inhibiting the expression of SDF-1 and CXCR4 in the sera of APOE mice, regulating blood lipid levels in atherosclerotic rats and interfering with the activities of key proteins in the PI3K/Akt/NF-κb pathway.[19] [20] In addition, luteolin also can reduce atherosclerosis by reducing inflammation in APOE mice.[21]

TNF is a cytokine that can directly kill tumor cells and exerts antitumor effects by activating the immune system. Ubiquitin-specific protease 20 can inhibit smooth-muscle cell inflammation caused by TNF overexpression by deubiquitinating β and relieving atherosclerosis.[22] IL-6 is a pleiotropic cytokine expressed by immune cells and various tumor cells. IL-6 induces inflammation, promotes cancer cell proliferation, and inhibits apoptosis, thereby promoting chemotherapy resistance. Studies have shown that IL-6 promotes the progression of Ewing's sarcoma by increasing resistance to apoptosis and promoting metastasis under cellular stress.[23] Inflammation is a major factor leading to atherosclerosis. IL-6 is an upstream inflammatory cytokine that plays a central role in downstream inflammatory responses leading to atherosclerosis.[24] MAPK1 is a member of the MAP kinase family and is also known as ERK2. MAPK1/ERK2 is involved in processes such as cellular proliferation, differentiation, and transcriptional regulation. Most patients with angiosarcoma have obvious genetic changes related to the MAPK signaling pathway, which activates the MAPK pathway and increases tumor cell proliferation. In the occurrence and development of alveolar rhabdomyosarcoma, HGF/MET signaling (mainly through ERK2 signaling) promotes the cellular motility and participates in the occurrence, invasion, and metastasis of tumor cells.[25] [26] MAPK1 is expressed in platelets and is activated by various agonists. Agonist-induced phosphorylation of MAPK1 can inhibit platelet aggregation; furthermore, loss or down-regulation of MAPK1 up-regulates VCAM-1 expression stimulated by insulin and TNF-α, leading to vascular disease.[27] [28]

The AGE-RAGE signaling pathway not only causes oxidative stress, inflammation, thrombosis, and fibrosis in a variety of cells but also activates a variety of signal transduction pathways related to cellular proliferation and apoptosis. Furthermore, the AGE-RAGE signaling pathway plays an important role in the occurrence, development, and metastasis of tumors.[29] [30] The IL-17 signaling pathway not only participates in autoimmune diseases and chronic inflammatory diseases but also participates in tumor cell survival, angiogenesis, chemokine production, tissue remodeling, and immune modification of the tumor microenvironment, thereby affecting the occurrence and development of STS and ASO.[31] [32] [33] [34] The HIF-1 signaling pathway participates in the regulation of angiogenesis, cellular metabolism, and autophagy, as well as in the occurrence or development of malignant tumors and inflammatory responses. Some studies have shown that the HIF-1 signaling pathway affects cellular metabolism, differentiation, angiogenesis, proliferation, and metastasis and this pathway is related to the prognosis of patients with STS and chondrosarcoma.[35] [36] The HIF-1 signaling pathway can also cause endothelial cell dysfunction, angiogenesis, and inflammation by up-regulating VEGF, NO, ROS and PDGF. Moreover, these responses play a role in the development of ASO.[37] Cytokines are small polypeptides or glycoproteins that are synthesized and secreted by a variety of cells and include interleukins, interferons, chemokines, growth factors, the tumor necrosis factor superfamily and colony-stimulating factors. Interactions between cytokines and cytokine receptors can regulate the growth and differentiation of cells, regulate immune responses, participate in inflammatory responses, repair damaged tissues, and have regulatory effects on STS and ASO.[38] [39] [40] [41] In addition, TNF signaling pathway, Th17 cell differentiation, and NOD-like receptor signaling pathway are all signal pathways related to immunity and inflammation, which can activate NF-κB, MAPK, and endoplasmic reticulum emergency pathway and promote the release of inflammatory factors such as IL-6 and mediate inflammatory response, which is closely related to tumors, inflammatory diseases, and autoimmune diseases.[42] [43]


Conclusions

In summary, this study reveals that the mechanism of YHD in the treatment of STS and ASO mainly involves cell proliferation, differentiation, angiogenesis, inflammation, immune response, oxidative stress, and other related signal pathways, which is consistent with the current research on the mechanism of STS and ASO. To some extent, it is proved that the results predicted by the network pharmacology method are reliable, but further experimental verification is still needed. This study can not only guide the experimental research in the next stage but can also provide a reliable basis for clinical application and new drug development.



Conflict of Interest

The authors declare no conflict of interest.

Credit Authorship Contribution Statement

Yiran Zhai: Conceptualization, methodology, data curation, formal analysis, and writing original draft. Binyi Li and Lili Miao: Writing - review & editing. Shanshan Li and Jie Wang: Formal analysis. Shiqing Jiang: Conceptualization, methodology, and supervision.



Address for correspondence

Shiqing Jiang, Professor
the First Affiliated Hospital of Henan University of Chinese Medicine
19 Renmin Road, Jinshui District, Zhengzhou, Henan 450046
China   

Publication History

Received: 10 May 2021

Accepted: 29 June 2021

Article published online:
28 July 2022

© 2022. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/)

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Fig. 1 Network of drugs–compounds–targets related to YHD in the treatment of STS/ASO. Notes: The regulatory network was constructed by 357 nodes (six Chinese herbs, 118 candidate compound nodes, and 233 target nodes) and 1,769 edges; among the 118 candidate compounds, eight compounds had no corresponding targets found in the database; purplish-red represents Chinese herbs, blue represents compound, yellow represents target,and the size of node is directly proportional to the Degree value of node.
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Fig. 2 Venn diagram of YHD targets in the treatment of STS and ASO.
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Fig. 3 Protein–protein interaction network of the common targets of YHD and STS/ASO.
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Fig. 4 GO enrichment analysis.
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Fig. 5 KEGG signaling pathway enrichment analysis (top 20).
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Fig. 6 Network of compoundstargetspathways related to YHD in the treatment of STS/ASO. Notes: The network consists of 56 nodes (18 compounds,18 key common targets, and 20 pathway nodes) and 203 edges; purple represents the pathway, blue represents the compound, yellow represents the target, and the size of the node is directly proportional to the degree value of the node.