Exploring the Effect of Corydalis Yanhusuo on Hepatoc ellular Carcinoma Mechanism through Network Pharma cology,Molecular docking and In Vitro Experiments

doi:10.21203/rs.3.rs-3061541/v1

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Exploring the Effect of Corydalis Yanhusuo on Hepatoc ellular Carcinoma Mechanism through Network Pharma cology,Molecular docking and In Vitro Experiments

https://doi.org/10.21203/rs.3.rs-3061541/v1

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Object: The study was conducted using network pharmacology (NP) and experimental validation as a base to identify potential targets and mechanisms of action of Corydalis yanhusuo (YHS) in treating Hepatocellular Carcinoma (HCC).

Methods: Traditional Chinese Medicine Systems Pharmacology (TCMSP) databasewas utilized to select effective YHS components, while the SymMap database was used to predict target proteins associated with effective components, and genes that could be related to HCC were selected using the GeneCards database. The Venn platform was used to obtain targets shared by YHS and HCC. Later, a String webserver was used to build protein-protein interaction (PPI) network, while a drug-component-target network was created using Cytoscape. GO and KEGG analysis was performed to parse biological processes and linked pathways connected to YHS in the treatment of HCC. Molecular docking technology was used to analyze the optimal effective components. The in vitro experiment on the HepG2 cell model confirmed the NP results.

Results: In total, 48 effective components and 88 shared targets were obtained. The main active ingredients identified were quercetin, hyndarin, isocordinine, (S)-Scoulerine, leonticine, and (R)-Canadine. The target-pathway network had 11 proteins and 211 pathways. Hub genes, in the PPI network included TP53, TNF, AKT1, MAPK1, IGF2, CDKN2A, TGFB1, MYC, CASP8, IL6, and CASP3. Moreover, as revealed by GO and KEGG analysis, Hepatitis B, the MAPK pathway, and the TNF pathway were all strongly linked to YHS's impact on HCC. Moreover, as demonstrated by in vitro experiments, YHS displayed remarkable activity in the treatment of HCC, most likely by regulating cell growth and apoptosis via MAPK pathways.

Conclusion: The present work suggests that NP-based analyses combined with experimental validation provide an efficient approach for characterizing the mechanism of YHS in the treatment of HCC.

Biological sciences/Cancer

Biological sciences/Computational biology and bioinformatics

Biological sciences/Drug discovery

Corydalis yanhusuo

network pharmacology

Molecular docking

Hepatocellular Carcinoma

Hepatocellular Carcinoma (HCC) is the sixth most common cancer in terms of morbidity and the third most common cause of cancer-associated deaths worldwide ¹. Currently, the main problems related to HCC treatment are drug resistance and complications after liver transplantation, surgery, transcatheter arterial chemoembolization (TACE), and radiofrequency ablation (RFA) ^{2, 3}. Despite significant advances in HCC treatment over the last few decades, more effective antitumor therapeutic strategies with low toxicity are needed.

TCM herbal medicines have been shown to reduce drug resistance and complications, reduce clinical symptoms, and extend tumor patient survival when used as monotherapies or adjuvant therapies. Corydalis yanhusuo (YHS) is a common TCM drug pair that can be used to treat tumors ⁴. According to previous research, the active ingredient in YHS is Dehydrocorydaline, which can suppress cell growth, invasion, and migration by inhibiting the MEK1/2-ERK1/2 cascade within melanoma ⁵. Besides, 13-methyl-palmatrubine has been shown to trigger cell cycle arrest and apoptosis in A549 cells both in vivo and in vitro ⁶. l-THP has a potent effect on reducing xenograft HepG2 tumor development in nude mice while not affecting other organs ⁷. Another study by TIAN revealed that YHS increased cell apoptosis and decreased cell viability by activating ROS-mediated endoplasmic reticulum stress (ERS) within colorectal cancer (CRC) cells ⁸. Yanhusuo extract has been shown to inhibit breast cancer (BC) cell metastasis by modulating the MAPK pathway ⁹. The potential antitumor treatment is YHS in combination with the corresponding effective ingredients. Nonetheless, the chemical and pharmacological mechanisms by which YHS inhibits human cancers, particularly HCC, are still largely unknown. Consequently, this research focused on the effect of YHS’ on HCC resistance as well as the underlying mechanisms.

The network pharmacology (NP) method was used in this study to investigate and predict bioactive components, as well as potential protein targets and pathways of YHS on HCC. Verification experiments were also carried out, according to NP analysis. Figure 1 presents the technical strategy used in this work.

Network Pharmacology (NP)

The TCMSP database (https://tcmsp-e.com) was used to obtain information on YHS bioactive compounds ¹⁰. To retrieve compounds, drug-likeness (DL) ≥ 0.18 and oral bioavailability (OB) ≥ 30% were used ^{11, 12}. For identifying compound-related targets, SymMap (https://www.symmap.org/) ¹³ and the TCMSP database were used, while duplicates and targets with zero probability were eliminated.

Prediction of HCC-Related Targets

The HCC-related targets were identified using the GeneCards database (https://www.genecards.org/) ¹⁴, with a score ≥ 55. Targets shared by YHS and HCC were obtained using the Venn platform (http://bioinformatics.psb.ugent.be/webtools/Venn/) ¹⁵.

Network Establishment

PPI networks were established using the String platform (https://string-db.org/), based on target proteins shared by YHS and HCC ¹⁶, with the parameters of the medium confidence score being 0.4 for the human species. To obtain a drug-ingredients- targets-disease network and conduct network analysis, we entered information about compounds and shared targets into Cytoscape 3.9.1. Then Cytoscape plug-in NetworkAnalyzer was used to evaluate topological parameters for nodes, such as betweenness centrality (BC), the closeness of centrality (CC), and degree centrality (DC).

GO and KEGG Analyses

Based on DAVID Bioinformatics Resources 6.7 (http://david.abcc.ncifcrf.gov/), gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed ¹⁷. During functional annotation, we used the standard Expression Analysis Systematic Explorer (EASE) threshold scores ≤ 0.05 and Count ≥ 2.

Molecular Docking (MD)

Based on the HCC-YHS-possible target network, quercetin and hyndarin were selected for docking with TNF-α and P38-MAPK proteins using Vina 1.1.2. PDF files for TNF-α and P38-MAPK and the two ingredients were imported to the CB-Dock website. After determining docking pocket coordinates, CB-dock was used for conformational scoring and MD. Vina score was used to evaluate compound-target binding with a low score indicating stable ligand-receptor binding.

Experimental Verification

Quercetin and hyndarin preparation. Zhongshan Chinese Traditional Medicine Co. (Nanjing, China) supplied quercetin and hyndarin, which were identified by a Chinese pharmacist.

Cell Culture

HepG2 cells were obtained commercially from the American Type Culture Collection (ATCC; Manassa, VA, USA), and cultured in DMEM containing 1% penicillin-streptomycin (PS) and 10% FBS under 37°C and 5% CO₂.

Cell Viability Assay

HepG2 cells (3,000/well) were seeded into 96-well plates and incubated for 48 h. Cells were then pretreated for a period of 48 h with different doses of quercetin (0, 10, 20, 40, 50, 100, 200,400, 800, 1000, and 2000 µg/mL) and hyndarin (0, 5, 10, 20, 40, 80,160, 320, 640, and 1280 µM) followed by the addition of 10 µL CCK-8 solution (Nuosaiwei, China) into each well and incubated for next 4 h under 37°C. Following incubation, the supernatant of each well was discarded, and DMSO (100 µL) was added. At 450 nm, optical density (OD) values were determined using a Multiskan MS microplate reader (Labsystems, Finland).

Clone Forming Assay

HepG2 cells (3,000/well) were seeded into the 6-well plates followed by 48 h incubation. Following that, cells were exposed or not to quercetin (150, 300 µg/mL) and hyndarin (90,180 µM) for the next 14 days. After a 15-min fixation with 4% paraformaldehyde (PFA), crystal violet solution was added at room temperature as a part of10 min cell staining procedure. To determine colony number, cell colonies were rinsed with water and photographed (100 or more cells).

Flow Cytometry (FCM) for Cell Apoptosis Analysis

HepG2 cells (5 × 10⁵/well) were seeded into 6-well plates. After 12 h, serum-free DMEM was added to replace the original medium for another 12 h, followed by 48 h cell exposure or no exposure to quercetin (150 and 300 µg/mL), and hyndarin (90 and 180 µM). After that, a FITC-coupled Annexin-V apoptosis kit was used for cell staining, and FCM was performed to analyze cell apoptosis.

MAPK/TNF Protein Expression Analysis

According to 2.2.5 cell processing procedures, HepG2 Cells or supernatants were collected and processed by the instructions of the MAPK/TNF protein kit. After the reaction time, the OD value was determined using a Multiskan MS microplate reader.

Statistical Analysis

For statistical analysis, the Prism 8 software was used. Results were represented as mean ± SD and compared using the student’s t-test. P value < 0.05 denoted statistical significance. Each experiment was repeated thrice or more.

NP analysis

Bioactive Components and Associated Targets in YHS

TCMSP was used to search and collect 77 components in total. A total of 48 components were identified based on YSH components (OB ≥ 30%, DL ≥ 0.18) (Table 1). There were 183 targets estimated in YHS via the SymMap database.

Table 1

Effective components of *Corydalis yanhusuo*.
Molecule ID	Molecule name	Molecular weight	OB (%)	DL
MOL001454	berberine	336.39	36.86	0.78
MOL001458	coptisine	320.34	30.67	0.86
MOL001460	Cryptopin	369.45	78.74	0.72
MOL001461	Dihydrochelerythrine	349.41	32.73	0.81
MOL001463	Dihydrosanguinarine	333.36	59.31	0.86
MOL001474	sanguinarine	332.35	37.81	0.86
MOL000217	(S)-Scoulerine	327.41	32.28	0.54
MOL002670	Cavidine	353.45	35.64	0.81
MOL002903	(R)-Canadine	339.42	55.37	0.77
MOL000359	sitosterol	414.79	36.91	0.75
MOL004071	Hyndarin	355.47	73.94	0.64
MOL004190	(-)-alpha-N-methylcanadine	354.46	45.06	0.8
MOL004191	Capaurine	371.47	62.91	0.69
MOL004193	Clarkeanidine	327.41	86.65	0.54
MOL004195	CORYDALINE	369.5	65.84	0.68
MOL004196	Corydalmine	340.45	52.5	0.59
MOL004197	Corydine	341.44	37.16	0.55
MOL004198	18797–79–0	367.43	46.06	0.85
MOL004199	Corynoloxine	365.41	38.12	0.6
MOL004200	methyl-[2-(3,4,6,7-tetramethoxy-1-phenanthryl)ethyl]amine	355.47	61.15	0.44
MOL004202	dehydrocavidine	351.43	38.99	0.81
MOL004203	Dehydrocorybulbine	352.44	46.97	0.63
MOL004204	dehydrocorydaline	366.47	41.98	0.68
MOL004205	Dehydrocorydalmine	338.41	43.9	0.59
MOL004208	demethylcorydalmatine	327.41	38.99	0.54
MOL004209	13-methyldehydrocorydalmine	352.44	35.94	0.63
MOL004210	(1S,8'R)-6,7-dimethoxy-2-methylspiro [3,4-dihydroisoquinoline-1,7'-6,8-dihydrocyclopenta [g] [1, 3]benzodioxole]-8'-ol	369.45	43.95	0.72
MOL004214	isocorybulbine	368.51	40.18	0.66
MOL004215	leonticine	327.46	45.79	0.26
MOL004216	13-methylpalmatrubine	352.44	40.97	0.63
MOL004220	N-methyllaurotetanine	341.44	41.62	0.56
MOL004221	norglaucing	341.44	30.35	0.56
MOL004224	pontevedrine	381.41	30.28	0.71
MOL004225	pseudocoptisine	320.34	38.97	0.86
MOL004226	24240–05–9	353.4	53.75	0.83
MOL004228	saulatine	396.47	42.74	0.79
MOL004230	stylopine	323.37	48.25	0.85
MOL004231	Tetrahydrocorysamine	337.4	34.17	0.86
MOL004232	tetrahydroprotopapaverine	329.43	57.28	0.33
MOL004233	ST057701	341.44	31.87	0.56
MOL004234	2,3,9,10-tetramethoxy-13-methyl-5,6-dihydroisoquinolino [2,1-b]isoquinolin-8-one	381.46	76.77	0.73
MOL000449	Stigmasterol	412.77	43.83	0.76
MOL000785	palmatine	352.44	64.6	0.65
MOL000787	Fumarine	353.4	59.26	0.83
MOL000790	Isocorypalmine	341.44	35.77	0.59
MOL000791	bicuculline	367.38	69.67	0.88
MOL000793	C09367	325.39	47.54	0.69
MOL000098	quercetin	302.25	46.43	0.28

HCC Targets Prediction as well as Shared Targets

Based on the GeneCards database, 17613 HCC-related targets were identified. We showed 88 genes to be potential therapeutic targets using scores ≥ 55 as the screening condition. The YHS targets were compared with HCC targets, and the Venn diagram shows that there were 12 shared targets (Fig. 2A). The obtained shared targets were YHS’s potential anti-HCC targets.

PPI Network Construction and Drug-Components-Targets

These 12 shared targets were entered into the String database to create the target PPI prediction network (Fig. 2B). With the elimination of isolated target proteins for obtaining protein interaction data, the confidence level was > 0.4. The drug-ingredient-target network was created by Cytoscape to obtain relationships of effective components with shared targets and HCC (Fig. 3). The drug-ingredient-target network had 231 nodes and 702 edges. Quercetin (MOL000098, degree = 150), Isocorypalmine (MOL000790, degree = 21), Hyndarin (MOL004071 degree = 20), (S)-Scoulerine (MOL000217, degree = 19), leonticine (MOL004215, degree = 18), and (R)-Canadine (MOL002903, degree = 17) were identified as an important active compound. Important anti-HCC therapeutic targets identified were PTGS2 (degree = 47), PTGS1 (degree = 43), SCN5A (degree = 42), KCNH2 (degree = 39), CALM3 (degree = 36), RXRA (degree = 31), ADRB2 (degree = 29), OPRD1 (degree = 28), and OPRM1 (degree = 28). Based on the above findings, the targets were closely linked to others in the network, which could have significant implications for HCC.

GO and KEGG Analysis

We used the DAVID database to analyze GO and KEGG enrichment on 12 shared targets. Altogether 118 biological processes (BP), 10 cellular components (CC), and 19 molecular functions (MF) terms were enriched, and they met the EASE scores ≤ 0.05 and Count ≥ 2. Figure 4A-4C shows 10 significant GO terms. Typically, the above genes were enriched in BP terms such as cellular response to organic cyclic compounds, positive regulation of gene expression and transcription using DNA as a template, protein complexes, mitochondria, cytosol, transcription factor binding, and protein binding. Therefore, YHS can be used to treat HCC by regulating cancer cell proliferation through various gene biological activities. KEGG enrichment on the target was done to identify the underlying pathways related to the treatment of HCC by YHS. Figure 4D shows the top ten pathways enriched using KEGG. The enriched pathways were closely related to YSH, like, for example, TNF and MAPK pathways.

Target-Pathway Network and Analysis

To characterize the YSH-related mechanism in the treatment of HCC, we built a target-pathway network with 11 proteins (NFE2L2 removed) and the associated pathways (Fig. 5). It covered 21 nodes and 70 edges (11 and 10 for proteins and pathways separately). The Hepatitis B pathway, cancer pathways, TNF pathway, and MAPK pathway were the most significant, with the highest degree values (Table 2). AKT1, MAPK1, CASP3, and TNF had high levels and had important effects on cell growth, making them a critical therapeutic target in YHS for treating HCC.

Table 2

Topological structure analysis of the targets-pathways network of *Corydalis yanhusuo* targeting HCC.
Node	Degree	Betweenness	Closeness
Hepatitis B	9	0.071848	0.606061
AKT1	10	0.098886	0.666667
MAPK1	10	0.098886	0.666667
CASP3	8	0.055394	0.588235
IL6	5	0.015682	0.47619
TNF	7	0.039278	0.526316
CASP8	6	0.023456	0.5
TP53	6	0.029093	0.526316
MYC	6	0.029093	0.526316
TGFB1	9	0.077105	0.625
Proteoglycans in cancer	8	0.131336	0.571429
IGF2	1	0	0.37037
Pathways in cancer	9	0.116906	0.606061
CDKN2A	2	0.001548	0.4
Colorectal cancer	6	0.01908	0.512821
Chronic myeloid leukemia	6	0.04642	0.512821
Tuberculosis	7	0.033935	0.540541
Chagas disease (American trypanosomiasis)	6	0.02507	0.512821
TNF signaling pathway	6	0.024763	0.512821
Toxoplasmosis	6	0.020358	0.512821
MAPK signaling pathway	7	0.031336	0.540541

Molecular Docking

The network pharmacology analysis revealed that quercetin and hyndarin interact with TNF-α and P38-MAPK at different levels (Fig. 6). The lower vina scores indicated a stable and potent compound-protein interaction. Vina scores for quercetin and hyndarin were less than − 0.6, indicating that quercetin and hyndarin had a stronger and more stable binding affinity for TNF-α and P38-MAPK. Consequently, quercetin and hyndarin were the suitable interacting partners for TNF-α and P38-MAPK protein.

Experimental Validation

Using network pharmacology analysis, quercetin and hyndarin were identified as important components of Corydalis yanhusuo in the treatment of HCC. Based on NP analysis, quercetin, and hyndarin were obtained. These two molecules were then validated for their role in resisting cancer cell proliferation.

For validation, HepG2 cells were treated for 48 h with quercetin and hyndarin. Following treatment, the IC50 values were found to be 178.8 µg/mL, and 413.4 µM, respectively. Quercetin and hyndarin also showed dose-dependent growth inhibition of HepG2 cells (Fig. 7A). Additionally, with the increase in doses of quercetin and hyndarin, the HepG2 clone number declined (p < 0.001) (Fig. 7B-C). Similarly, the HepG2 cell apoptosis degree was found to increase with an increase in quercetin and hyndarin concentration. Upon statistical comparison, the treatment group had increased apoptosis levels compared with the control group (p < 0.001) (Fig. 8). In vitro experiments yielded similar NP analysis results.

After 48-h of quercetin and hyndarin treatment of HepG2 cells, MAPK protein expression was down-regulated (p < 0.01), but MAPK and TNF protein levels within the HepG2 cells of the quercetin group were not statistically significant (Fig. 9), indicating that hyndarin has inhibitory effects on MAPK signaling pathways, and quercetin may have inhibitory effects on other pathways.

TCM is currently receiving worldwide attention for cancer prevention and treatment ¹⁸. Corydalis yanhusuo (YHS), a TCM drug pair, has a significant effect in the clinic by mitigating symptoms in HCC cases ⁷. However, the anti-HCC effects of YHS, as well as the underlying mechanisms, require further investigation. Therefore, network pharmacology and biological analysis were carried out to understand the possible mechanism of action of YHS.

Based on network pharmacology research, YHS is known to contain 48 active components. Components in YHS that met OB ≥ 30% and DL ≥ 0.18 criteria were pharmacokinetically active, indicating possible absorption and distribution in the human body. High-degree compounds in the compound-target network of YHS may have been the most effective in treating HCC. According to our findings, quercetin and hyndarin were identified as significant compounds. Quercetin, a naturally occurring flavonoid, has been shown to have anticarcinogenic properties by suppressing the PI3K pathway ¹⁹. By regulating PDCD4-mediated apoptosis, isocorydine targeted the drug-resistant cellular population in HCC ²⁰. Furthermore, by inhibiting ERK pathways, isocorydine could suppress doxorubicin-mediated epithelial-mesenchymal transition (EMT) in HCC ²¹. Hyndarin, a bioactive compound, has been shown to suppress hepatocellular carcinoma tumor growth via AMPK-mediated metabolic switching and in vitro and in vivo osteoclastogenesis by suppressing RANK-TRAF6 interactions along with NF-B and MAPK pathways ^{7, 22}. Although there was no literature relating (S)-Scoulerine, leonticine, and (R)-Canadine with HCC, they did report their effect on microtubule architecture, and growth inhibition, thereby causing cell cycle arrest and promoting apoptosis in tumor cells ^{23, 24}. All of these studies, along with ours, confirmed our NP analysis results and presented a reliable NP-based method to identify the TCM mechanisms.

According to gene target prediction and pathway enrichment, YHS may have achieved its anti-HCC efficacy by regulating cell growth. Pathways controlling several processes, such as cell growth, migration, invasion, and angiogenesis, are the primary anti-HCC therapeutic target source, and can frequently be abnormal during HCC occurrence and development. According to NP, YHS may treat HCC by modulating HCC cell growth via the MAPK and TNF pathways. This work investigated whether quercetin and hyndarin could treat HepG2 cells in vitro. According to our in vitro analysis, quercetin and hyndarin administration significantly reduced HepG2 cell viability and clone formation capacity, and induced HepG2 cell apoptosis in a dose-dependent manner. MAPK expression, in particular, remarkably declined, whereas TNF levels did not differ statistically. MAPK belongs to the MAPK family, which plays an important role in regulating HBV infection-related HCC cell growth via cell proliferation, differentiation, and apoptosis ²⁵. As a result, MAPK down-regulation following hyndarin pretreatment in HCC cells might facilitate its therapeutic efficacy. Collectively, this study suggests hyndarin as a suppressor of HCC development by regulating cell growth via MAPK signaling pathways. However, there are some shortcomings in this research. Furthermore, our next study will look into the YHS-related pharmacological mechanisms in the treatment of HCC.

Collectively, this study examined the YHS-related pharmacological mechanism in inhibiting HCC using NP-based analysis and experimental validation. According to our findings, hyndarin is an active component of YHS, that inhibits HCC growth and survival primarily through regulating MAPK pathways. According to preliminary research, NP-based analysis supported by experimental verification can provide an efficient way of characterizing the TCM mechanisms. More research is needed to analyze YHS efficacy in treating HCC cases.

Data Availability

All data used to support our results can be obtained from the corresponding author on request.

Conflicts of Interest

The author(s) declare(s) that there is no conflict of interest regarding the publication of this paper.

Disclosure

All funders did not participate in designing this work, collecting or analyzing data, preparing the manuscript, or making the decision of publication.

Funding Statement

The present work was funded by the Science Foundation of Anhui Province, China [grant number 2022AH052549].

Acknowledgments

Not applicable.

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No competing interests reported.

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Exploring the Effect of Corydalis Yanhusuo on Hepatoc ellular Carcinoma Mechanism through Network Pharma cology,Molecular docking and In Vitro Experiments

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Introduction

Materials and Methods

Network Pharmacology (NP)

Prediction of HCC-Related Targets

Network Establishment

Experimental Verification

Statistical Analysis

Results

NP analysis

Experimental Validation

Discussion

Conclusion

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References

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