Mechanisms underlying the therapeutic effects of Xiaoyaosan in treating hyperplasia of mammary glands based on network pharmacology

Abstract

This study utilized network pharmacology to investigate the effects of Xiaoyaosan (XYS) on the intervention of hyperplasia of mammary glands (HMG) by targeting specific genes and signaling pathways. The active ingredients and targets of XYS, which consisted of 8 traditional Chinese medicines (TCM), were identified using TCMSP. The gene targets associated with HMG were obtained from the GeneCards Database, and the intersection data between the 2 was integrated. Cytoscape 3.8.1 software was used to construct a network diagram illustrating the relationship between compounds, drug active ingredients, target proteins, and the disease. The protein-protein interaction network diagram was generated using STRING, and the core targets were analyzed. A total of 133 active ingredients in XYS and 7662 active ingredient targets were identified. Among them, 6088 targets were related to HMG, and 542 were common targets between the active ingredients and the disease. The protein-protein interaction (PPI) core network contained 15 targets, with 5 key targets playing a crucial role. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses have indicated that XYS has the potential to treat HMG by interfering with the AGE-RAGE signaling pathway in diabetic complications, the MAPK signaling pathway, and the PI3K-Akt signaling pathway. Additionally, molecular docking studies have shown excellent binding properties between the drug components and key targets. Thus, this study provides a theoretical foundation for a better understanding of the pharmacological mechanism and clinical application of XYS in the comprehensive treatment of HMG.

1. Introduction

Hyperplasia of the mammary gland (HMG), also referred to as mammary dysplasia, is a non-cancerous breast disease that occurs due to abnormal development and degeneration of the breast tissue. It is important to note that HMG is not caused by inflammation or tumors.^[1] The main cause of HMG is the secretion of estradiol (E2) and progesterone (P), which leads to excessive proliferation of mammary epithelial cells and breast tissue hyperplasia.^[2] This disease has a high potential for developing into breast cancer and may be diagnosed as early breast cancer. The incidence of cancer in HMG ranges from 2% to 4%. As a result, the treatment of this disease has become a research focus.^[3,4] Currently, western medications commonly used for treating HMG in clinical practice include hormonal agents, hormone receptor inhibitors, vitamins, and prolactin inhibitors.^[5] However, these treatments have serious side effects and complications, and the long-term efficacy of their application is questionable. Some common side effects may include delayed or stopped menstruation, leukorrhea, and nausea.^[6] Therefore, the development of alternative pharmacological therapies is important. Traditional Chinese medicine (TCM), which has been used for over 2 thousand years, offers a potential treatment options for HMG.^[7] According to TCM, the pathological basis of HMG is described as “qi ji bu chang,” and the pathogenesis involves “qi, blood, phlegm, and blood stasis.”^[8] Xiaoyaosan (XYS) which consists mainly of Angelica sinensis (Danggui, DG), Paeonia lactiflora (Baishao, BS), Cryptotaenia japonica (Chaihu, CH), Wolfiporia extensa (Fuling, FL), Atractylodes macrocephala (Baizhu, BZ), Licorice (Gancao, GC), Ginger (Shengjiang, SJ), and Cedarwood (Bohe, BH), is known for its ability to relax the liver, strengthen the spleen, regulate Qi, and resolve phlegm. Previous studies have indicated that XYS can protect the mammary gland and treat breast disease by mediating ERs and stimulating the expression of mRNA and ERβ.^[9] However, there is a lack of systematic investigation into the positive effects of XYS, including potential targets and mechanisms of action.

TCM comprises highly complex compounds that involve multiple pathological indicators and pathways. Therefore, traditional pharmacological approaches have limited actions in studying the mechanisms of TCM. In 2013, Shao Li proposed a new concept called “network pharmacology,” which offers a new strategy for determining the mechanism of action of TCM formulations.^[10] Network pharmacology is an emerging discipline based on the theory of systems biology and network analysis of biological systems. It involves the selection of specific signaling nodes to design multi-target drug molecules. The primary focus is on understanding disease mechanisms rather than clinical symptoms. By using 2 or more drugs that act mechanistically on the same pathogenic signaling disease module, network pharmacology-based therapies can synergistically target key network proteins. This approach allows for a significant reduction in the dose of each drug compared to monotherapy, while still achieving the same or even more significant therapeutic effects. Additionally, it helps in minimizing the side effects of each drug and potentially unnecessary medications.^[11–13] Based on its advantages, network pharmacology is a suitable method for analyzing TCM. The integration of bioinformatics has further enhanced the use of network pharmacology in studying the therapeutic effects of TCM in different diseases.

In this study, a network pharmacology approach was employed to predict the main active components, potential targets, and mechanisms of action of XYS in the treatment of HMG. The findings of this study serve as a foundation for further research on the mechanism of action of XYS in HMG treatment (Fig. 1).

Figure 1.

Flowchart.

2. Materials and methods

2.1. Data collection

2.1.1. Screening of active compounds of XYS.

The components of the 8 herbs were identified using the pharmacology of Traditional Chinese Medicine Systems Pharmacology (TCMSP,https://tcmspw.com/tcmsp.php)^[14] and then screened based on their oral bioavailability (OB ≥ 30%) and drug-likeness (DL ≥ 0.18).^[15] TCMSP is a comprehensive platform for herbal medicines, containing information on 499 Chinese herbs registered in the Chinese pharmacopeia. It includes 29,384 ingredients, 3311 targets, and 837 associated diseases.^[16] The platform also offers additional data on chemicals, targets, and drug-target networks, such as drug similarity, oral bioavailability, and blood-brain barrier permeability.^[17] TCMSP aims to facilitate the development of herbal medicines and promote the integration of modern medicine and traditional medicine for drug discovery and development. The techniques employed in the TCMSP platform have been successfully used in previous studies to investigate the mechanisms of action of herbal medicines and TCM formulas in treating cardiovascular diseases and viral diseases.^[18]

2.1.2. Acquisition of targets related to HMG.

The keywords “hyperplasia of mammary glands” were used to obtain disease-related targets in the GeneCards (https://www.genecards.org/) database.^[19]

2.1.3. Intersection between active compounds and disease targets.

The intersection targets between the HMG-related genes and the predicted XYS targets were obtained and Venny 2.1.0 (http://bioinfo.cnb.csic.es/tools/venny/index.html) was used to construct a Venn diagram for visualization.

2.1.4. XYS-active ingredient-target network construction.

Taking the drug-disease intersection, importing the intersection and the drug-active ingredient into Cytoscape 3.8.1 (https://www.cytoscape.org/),^[20] constructed the TCM-active ingredient-target network of XYS and HMG.

2.2. Protein-protein interaction (PPI) network construction

Intersecting targets were uploaded to the String database (https://www.string-db.org).^[21] The species selected was Homo sapiens, with a minimum interaction threshold set to 0.9. The default evidence type was used to establish a protein-protein interaction network. The network was imported into Cytoscape 3.8.1 software, and the Cytohubba plug-in was applied to calculate the maximum centrality MCC value of each node in the network for mapping the hub gene network.^[20]

2.3. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis

Crossover genes were analyzed for GO and KEGG enrichment using the Database for Annotation, Visualization and Integrated Discovery (David) (https://david.ncifcrf.gov/). The statistical significance was determined with FDR < .05 and P < .05.^[22]

2.4. Molecular docking verification of key targets and drug ingredients

To identify the top 5 hub target proteins in the PPI network based on degree values, we downloaded their 3D structures in SDF format from PubChem data (https://pubchem.ncbi.nlm.nih.gov/). These structures were then imported into ChemBio3D Ultra 14.0 (http://china.cambridgesoft.com/Ensemble_for_Chemistry/ChemBio3D/Default.aspx) for energy minimization. The optimized small molecules were further imported into AutodockTools-1.5.6 (http://www.autodock.scripps.edu) for hydrogenation, charge calculation, charge assignment, setting rotatable keys, and saving them in “pdbqt” format. We obtained the following protein structures from the PDB database (https://www.rcsb.org): MAPK1 (PDB ID: 2Y9Q), AKT1 (PDB ID: 6NPZ), JUN (PDB ID: 5T01), MAPK3 (PDB ID: 4QTB), and STAT3 (PDB ID: 6NJS). After removing protein crystalline water, raw ligands, etc, the protein structures were imported into AutoDocktools (v1.5.6) for hydrogenation, charge calculation, charge assignment, and atom type assignment, and saved as “pdbqt.” Finally, the docking results were analyzed for interaction patterns using PyMOL 2.3.0 (https://pymol.org/2/).

3. Results

3.1. Network analysis of XYS and HMG targets

Based on the screening conditions, 133 active ingredients of XYS were screened in TCMSP, resulting in 7662 active ingredient targets and 6088 HMG-related targets. Among these targets, 542 were found to be common to both the active ingredients and the diseases (Fig. 2). The network diagram of XYS and HMG targets was generated using Cytoscape 3.8.1 (Fig. 3). To further understand the relationship between TCM and diseases, the top 5 active ingredients were ranked based on their degree value (Fig. 4, Table 1). The identified active ingredients were MOL000098 (quercetin), MOL000422 (kaempferol), MOL000006 (luteolin), MOL004328 (naringenin), and MOL000497 (licochalcone a). Therefore, it is hypothesized that XYS may exert its therapeutic effects on HMG by targeting these 5 active ingredients.

Figure 2.

Venn diagrams of XYS - HMG common targets. HMG = hyperplasia of mammary glands, XYS = Xiaoyaosan.

Figure 3.

“Ingredient-disease-target” network of XYS from Cytoscape. XYS = Xiaoyaosan.

Figure 4.

Top 5 MOLID with degree values.

Table 1.

Table of key ingredient information.

MOL ID	NAME	Average shortest path length	Betweenness centrality	Closeness centrality	Degree
MOL000098	Quercetin	1.864 583	0.145358	0.536 313	111
MOL000422	Kaempferol	2.329 861	0.029 727	0.429 21	39
MOL000006	Luteolin	2.392 361	0.020 97	0.417 997	36
MOL004328	Naringenin	2.503 472	0.013 478	0.399 445	26
MOL000497	Licochalcone-a	2.482 639	0.008 962	0.402 797	23

3.2. Analysis of XYS core targets for HMG treatment

The 542 intersecting targets were imported into the String database and filtered based on the specified conditions. The PPI network was then constructed for the biological species “Homo sapiens” with a confidence level >0.9. The resulting PPI network consisted of 169 nodes and 698 edges, with an average degree value of 8.26. Figure 5 displays the PPI network obtained from the String website, while Figure 6 presents the PPI network created using Cytoscape software.

Figure 5.

PPI network of HMG target and XYS target from STRING. HMG = hyperplasia of mammary glands, PPI = protein-protein interaction, XYS = Xiaoyaosan.

Figure 6.

PPI network of HMG target and XYS target from Cytoscape. HMG = hyperplasia of mammary glands, PPI = protein-protein interaction, XYS = Xiaoyaosan.

To identify the core target points in the PPI network, the Hubba plug-in in Cytoscape was utilized. The combined degree value of each node in the network was calculated, and the top ten nodes with the highest degree values were considered as the core target points for picture mapping (Fig. 7), where the horizontal coordinate represents the degree value of each target point.

Figure 7.

Top 10 targets with degree values.

For the core targets in the picture drawing, the horizontal coordinate represents the degree value of each target (Fig. 8). These 10 core proteins, namely STAT3, AKT1, MAPK1, JUN, MAPK3, RELA, IT6, MAPK14, MAPK8, and ESR1, are potential targets of XYS for the treatment of HMG.

Figure 8.

BP bubble diagram. BP = biological process.

3.3. GO functional enrichment analysis

The above 542 intersecting targets were imported from the DAVID database to obtain the entries of biological process (BP), cellular component (CC), and molecular function (MF). A filtering condition of P < .05 was set, and the top twenty key targets were selected from each of the BP, CC, and MF (Figs. 8, 9, and 10). Bubble diagrams for GO function enrichment analysis were generated using Microbioinformatics (www.bioinformatics.com.cn) to visualize the results.

Figure 9.

CC bubble diagram. CC = cellular component.

Figure 10.

MF bubble diagram. MF = molecular function.

The enrichment analysis revealed a total of 1344 BP , 318 molecular functionally related processes, and 1344 cellular compositionally related processes. The key BP associated with XYS treatment for HMG were protein phosphorylation, negative regulation of apoptotic processes, and positive regulation of cell proliferation. These processes included phosphorylation, protein autophosphorylation, peptidyl-serine phosphorylation, peptidyl-cystine phosphorylation, and negative regulation of apoptotic processes. Additionally, processes such as positive regulation of cell proliferation, peptidyl-tyrosine phosphorylation, response to xenobiotic stimuli, inflammatory response, transmembrane receptor protein tyrosine kinase signaling pathway, and protein tyrosine kinase signaling pathway were also observed. The analysis also identified several CC that were prominently associated with XYS treatment for HMG, including the plasma membrane, cytosol, membrane rafts, macromolecular complexes, cytoplasmic extra-nuclear regions, cellular exosomes, and cell surface. Furthermore, the top MF identified were protease serine/threonine/tyrosine kinase activity, ATP binding, protein tyrosine kinase activity, protein binding, RNA polymerase II transcription factor activity, and ligand-activated sequence-specific DNA binding.

3.4. KEGG pathway enrichment analysis

Using the DAVID database, we imported the 542 intersecting targets and performed KEGG pathway enrichment analysis on the drug-disease common targets. The screening condition was set as P < .05, and the top 20 key targets were selected (Fig. 11). We generated the KEGG pathway enrichment analysis bubble diagram using Microbioinformatics (www.bioinformatics.com.cn).

Figure 11.

KEGG pathway Enrichment analysis bubble diagram. KEGG = Kyoto encyclopedia of genes and genomes.

A total of 187 pathways were enriched, primarily including pathways in cancer, lipid, and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, MAPK signaling pathway, PI3K-Akt signaling pathway, and others.

3.5. Results of molecular docking

In this study, we conducted molecular docking to confirm the binding activity of key active ingredients and targets, as shown in Table 2. The molecular docking process is illustrated in Figure 12. The results of the molecular docking validation of the key active ingredients with the core target all yielded negative realistic molecular docking binding energies, indicating spontaneous binding between the receptor and ligand. A higher affinity energy indicates poorer binding, while a lower affinity energy indicates better binding. The affinity energy results of small molecule-target docking reveal favorable binding energy between the core active ingredients and key targets, suggesting the multi-component and multi-target qualities of TCM in exerting clinical efficacy.

Table 2.

Molecular docking result of the key target.

Molecular name	Hub gene binding energy (kcal/mol)
	MAPK1	AKT1	JUN	MAPK3	STAT3
Kaempferol	−9.1	−7.9	−5.8	−9	−7.2
Licochalcone-a	−8.2	−8	−6.1	−9.2	−6.4
Luteolin	−9	−8.4	−6	−9.3	−7.6
Naringenin	−8.8	−8.3	−5.9	−9	−7.1
Quercetin	−9	−8	−6	−9.1	−7.4

Figure 12.

Molecular docking.

These results indicate that XYS acts on different pathways through different targets to treat HMG. Additionally, XYS may also have some efficacy in treating pancreatic cancer, endocrine resistance, and Kaposi sarcoma-associated herpesvirus infection, expanding the therapeutic scope of XYS.

4. Discussion

HMG, belonging to the category of “Rupi” in TCM, is characterized by symptoms such as breast pain, breast lumps, mood swings, and changes in the menstrual cycle. HMG has the highest incidence of clinical breast diseases, and if left untreated, it can potentially develop into breast cancer.^[23] However, the exact mechanism of action of XYS in treating HMG is still unknown. This study aims to analyze the mechanism of XYS on HMG using network pharmacology.

By constructing a “drug-disease-target” network, the top 5 key targets identified were STAT3, AKT1, MAPK1, JUN, and MAPK3. STAT3, being a convergence point of various oncogenic signaling pathways, plays a central role in regulating anti-tumor immune responses. It is over-activated in both cancerous and non-cancerous cells, leading to the suppression of key immune-activating regulators and the promotion of immunosuppressive factors.^[24] AKT1 has been experimentally shown to treat breast-like diseases by regulating EMT, apoptosis, and senescence.^[25] Down-regulating MAPK1 expression can inhibit the MAPK signaling pathway, promote apoptosis, inhibit the growth of TNBC cells in vitro, and impede tumor growth in vivo, thereby offering a potential treatment for HMG.^[26]

Quercetin, kaempferol, luteolin, naringenin, and licochalcone A are key components of XYS used in the treatment of HMG. Quercetin, a dietary flavonoids, has been widely demonstrated to inhibit tumor progression in everyday foods through various mechanisms. These mechanisms include enhancing apoptosis, blocking the cell cycle, inhibiting metastasis and angiogenesis, replicating antioxidants, and modulating estrogen receptors.^[27] Kaempferol, a major flavonoid glycoside, is found in many natural products such as legumes, bee pollen, broccoli, cabbage, cauliflower, chia seeds, onions, cumin, fennel, and garlic. It possesses a wide range of pharmacological properties, including antimicrobial, anti-inflammatory, antioxidant, antitumor, and neuroprotective properties. Kaempferol-rich foods have been associated with a reduced risk of certain types of cancers, such as skin, liver, and colon cancers. They have also been found to induce apoptosis, arrest the cell cycle at the G2/M phase, down-regulate epithelial-mesenchymal transition (EMT)-related markers, and affect the phosphatidylinositol 3-kinase/protein kinase B signaling pathway.^[28] Naringenin, a flavonoid widely distributed in citrus and tomato, inhibits autophagy and proliferation of breast cancer cells in vitro and in vivo through the FKBP4/NR3C1/NRF2 signaling pathway. Naringenin also promotes dendritic cell (DC) differentiation and maturation through the FKBP4/NR3C1/NRF2 axis.^[29] Licochalcone A (LCA), isolated from the roots of Glycyrrhiza glabra, is known to have antioxidant, antimicrobial, antiviral, and anticancer medicinal effects. It has been shown to have dose- and time-dependent anti-proliferative and apoptotic effects in breast cancer cells by regulating Sp1 and apoptosis-related proteins.^[30] Protein blotting analysis demonstrated that LCA effectively modulates the LC3-II signaling pathway, inhibits the PI3K/Akt/mTOR signaling pathway, enhances cysteine asparaginase-3 activity, and significantly reduces B-cell lymphoma-2 expression.^[31]

GO and KEGG enrichment analyses revealed that XYS has a potential therapeutic role in HMG by interfering with the AGE-RAGE signaling pathway in diabetic complications, as well as the MAPK and PI3K-Akt signaling pathways. Advanced glycosylation end products (AGEs) are formed through non-enzymatic reactions between free-reducing sugars and proteins, lipids, or nucleic acids, primarily during chronic hyperglycemia or aging. The AGE-RAGE signaling pathway has been implicated in the progression of various cancers and other pathological diseases. RAGE expression increases significantly during cancer progression, and activation of the AGE-RAGE signaling disrupts cellular redox homeostasis and regulates multiple cell death pathways.^[32] Key proteins present in XYS, such as MAPK1 and STAT3, play a role in the AGE-RAGE signaling pathway for HMG treatment. Although the AGE-RAGE signaling pathway has been extensively studied in diabetes treatment, its mechanism in HMG treatment remains largely unexplored. Therefore, further research in this area is of great significance and value. The MAPK signaling pathway, a major regulator of cellular processes including proliferation, differentiation, and stress responses, is also involved in tumorigenesis through mutations and dysregulation of key molecules.^[33] XYS contains key proteins like MAPK1 and MAPK3 that participate in the MAPK signaling pathway.^[34]

Based on the analysis above, it is evident that the primary mechanism of action in the treatment of HMG by XYS is through immunomodulation, anti-inflammatory effects, and reduction of oxidative stress. The modulation of sex hormones is not observed, indicating that while TCM exhibits characteristics such as multi-components and multi-targets, the immunomodulatory and anti-inflammatory effects likely play a more significant role in the treatment process of XYS for HMG.

5. Conclusion

In this study, it was found that quercetin, kaempferol, luteolin, and other components of XYS have the potential to regulate various signaling pathways, including the AGE-RAGE signaling pathway, MAPK signaling pathway, and PI3K-Akt signaling pathway. These pathways are involved in processes such as oxidative stress, anti-inflammation, regulation of apoptosis, and improvement of immunity. The core targets and genes, such as STAT3, AKT1, MAPK1, and HTR2A, play a crucial role in mediating these effects. The findings suggest that XYS may have therapeutic potential in the treatment of gynecological and other diseases, particularly in inhibiting the occurrence and development of HMG.

However, it is important to acknowledge the limitations of this study. Firstly, the decoction of TCM involves complex chemical reactions, which may affect the properties of the components. Additionally, the metabolism of drugs in the body can also alter their effects. Therefore, further research is needed to fully understand the mechanisms of action of XYS and to validate the identified targets.

Acknowledgments

We would like to thank Changchun University of Chinese Medicine for helpful discussions on topics relevant to this work. We also would like to thank the Editors and Reviewers for their helpful remark that improved this paper.

Author contributions

Conceptualization: Peizhe Li, Mingjun Liu.

Data curation: Sixian Wang, Shaowei Liu.

Formal analysis: Yuxing Tai, Long Zhang.

Methodology: Sixian Wang, Xin Li.

Software: Peizhe Li, Qifan Guan.

Supervision: Mingjun Liu.

Writing – original draft: Peizhe Li.

Writing – review & editing: Mingjun Liu.