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. 2023 Jul 14;102(28):e34300. doi: 10.1097/MD.0000000000034300

Mechanism of morusin on breast cancer via network pharmacology and in vitro experiments

Hangzhen Li a, Jianlei Xiao b, Xue Li c, Qian Huang d, Qingfeng Liu e, Qing Zhang f,g,*
PMCID: PMC10344534  PMID: 37443484

Background:

This study aimed to investigate the therapeutic effect of morusin on breast cancer and decode its underlying molecular mechanism using network pharmacology and in vitro techniques.

Methods:

Swiss Target Prediction and PharMmapper were applied to screen morusin targets. The targets of human breast cancer were obtained from the GeneCards database, and the overlapping targets were screened. A protein-protein interaction network was constructed based on the overlapping targets by String and Cytoscape. Performed Gene Ontology enrichment as well as Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis on the shared targets of the drug and disease using the David database. Additionally, performed molecular docking using PyMoL and AutoDock software. Finally, the impact of morusin on breast cancer was demonstrated by cell experiments and western blot.

Results:

A total of 101 target genes were obtained through screening including ESR1, EGFR, ALB, CTNNB1, AKT1, and so on. Based on the annotation of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, the anticancer properties of morusin are linked to apoptosis, migration, and PI3K-AKT signaling pathways. Molecular docking showed an interaction between morusin and PIK3CA, AKT1. In vitro data demonstrated that morusin causes apoptosis and inhibits cell migration. Morusin also increased the expression of cleaved-PARP while decreasing the expression of p-PI3K and p-AKT.

Conclusion:

Through network pharmacology analysis and in vitro experiments, this study showed that morusin promotes apoptosis and inhibits migration by modulating the PI3K-AKT axis. Morusin plays a key role in the treatment of breast cancer.

Keywords: apoptosis, breast cancer, migration, morusin, network pharmacology

1. Introduction

The high incidence of breast cancer has made it a more common cancer than lung cancer.[1] According to one study’s analysis, there will be roughly 3 million new cases of breast cancer diagnosed annually worldwide in 2040, an increase of >40%. Additionally, it is anticipated that >50% of people will die from breast cancer.[2] Depending on the type of cancer, breast cancer is treated using a variety of methods, including surgery, endocrine therapy, and chemotherapy.[3] Drug resistance causes many people to endure cancer recurrence and metastases despite initial positive findings.[4] Therefore, it is essential to discover viable alternatives to breast cancer.

The significance of Chinese medicine has increasingly come to light in recent years.[5,6] It has been demonstrated that the flavonoid morusin, which is produced from the white bark of mulberry roots, has anti-inflammatory, antibacterial, antiviral, and antioxidant properties.[7–9] Additionally, it has been demonstrated to have anticancer effects.[10,11] The precise mechanism of action of morusin’s anticancer effect on breast cancer, however, has not yet been identified.

Advances in bioinformatics based on network pharmacology and molecular docking allow us to rapidly identify drug therapeutic targets and mechanisms. Consequently, network pharmacology has emerged as an effective approach for unraveling the pharmacological mechanisms of new small-molecule drugs.[12–14]

Therefore, the function of morusin and the mechanisms underlying it in breast cancer were investigated by network pharmacology and molecular docking. In vitro experiments were also used to further demonstrate that morusin may be a strong contender for future breast cancer treatment.

2. Materials and methods

2.1. Potential targets of morusin

To identify and evaluate potential targets for morusin, the publicly available databases PharmMapper (https://www.lilab-ecust.cn/pharmmapper/index.html) and Swiss Target Prediction (http://www.swisstargetprediction.ch) were utilized. These databases were restricted to Homo sapiens as the only species. The identified target gene lists were standardized using UniProt (https://www.uniprot.org/) for further analysis.

2.2. Potential targets for breast cancer

The GeneCards database (https://www.genecards.org) incorporates a sizable quantity of data from the literature, covers the analysis dates of genes in other databases, and has all important data about the genes, making it the greatest tool for searching through human genetic information. From this database, breast cancer-related targets were obtained.

2.3. Protein-protein interaction (PPI) network model construction

Venn diagram of targets obtained using an online platform for data analysis and visualization (https://www.bioinformatics.com.cn) to look for prospective targets shared by morusin and breast cancer. The analysis results were then exported and performed as protein interaction prediction using the String database (https://www.string-db.org/). Finally, the core genes were discovered using Cytoscape 3.9.1 (https://cytoscape.org/).

2.4. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Enrichment Analysis

To identify the biological activities of possible targets and cancer-related pathways of morusin, the enrichment analysis of the GO and KEGG was obtained by DAVID database (https://david.ncifcrf.gov/). The top 20 KEGG pathway entries and the top 20 entries of molecular function (MF), cellular component, and biological process (BP) in GO, respectively, with a false discovery rate <0.05, were chosen for further visualization.

2.5. Molecular docking

Molecular docking is a tool for predicting the connection between targets and morusin. The likelihood of interaction between small-molecule drugs and probable targets can be evaluated using molecular docking, which models putative binding techniques and calculates the binding forces corresponding to them. The steps of molecular docking are approximate as follows: download the structure of morusin from TCMSP (https://old.tcmsp-e.com/tcmsp.php) and the relevant docking proteins as receptors from the UniProt (https://www.uniprot.org/); using the PyMol (https://pymol.org/2/), remove water and solvent molecules from proteins; process receptors and ligands further using the Auto Dock Tools before performing docking (perform 50 docking for each protein); using PyMol, the docking data with the lowest binding energies were chosen. A binding energy of 0 is typically taken to mean that the ligand and target protein can bind separately.

2.6. Reagents

Vicky Biotechnology Co., Ltd. supplied morusin (Cat No.62596-29-6, Sichuan, China). The Tong Ren Chemical Research Institute offered the CCK8 kit (Cat No.CK18, Dojindo, Japan). Apoptosis kits were obtained from BD Biosciences (Cat No.559763, BD Biosciences, USA). The BCA kits (P0010) and ultrasensitive ECL chemiluminescence kits (P0018AS) were purchased from Biyuntian Institute of Biotechnology (Shanghai, China). The antibodies for AKT (#4691T), p-AKT (#4060T), PI3K (#13666S), p-PI3K (#17366S), cleaved-PARP (#5625T), and β-ACTIN (#3700S) were provided by Cell Signaling Technology (CST, MA, USA).

2.7. Cells

MDA-MB-231, BT549, and Hs578T breast cancer cells were received from the Chinese Academy of Sciences Shanghai Institute of Cell Biology (Shanghai, China). In DMEM medium containing 1% streptomycin/puromycin and 10% fetal bovine serum, MDA-MB-231 and Hs578T cells were maintained. In 1640 medium with 1% streptomycin/puromycin and 10% fetal bovine serum as supplements, BT549 cells were grown. At 37°C and 5% CO2, all cells are grown in an incubator.

2.8. CCK8

MDA-MB-231 (5 × 104 cells/mL), BT549 (3 × 104 cells/mL), and Hs578T (2 × 104 cells/mL) cells were sown into 96 wells. The next day, cells were cultured in a medium with various drug concentrations (0, 2.5, 5, 10, 20, 40, 80 µmol/L) for 48 hours. Finally, the CCK8 detection reagent was added and incubated for 1 hour without light, and its absorbance value at 450 nm was determined.

2.9. Western blot

The samples were centrifuged at 12,000 g for 10 minutes at 4°C using a cryogenic high-speed centrifuge (Black Horse Medical Instruments Co., Ltd., Zhuhai, China) to retrieve the sample supernatant after the cells had been thoroughly lysed by RIPA lysis solution. Using a BCA kit, protein concentration can be determined. The same mass of sample was put into a polyacrylamide gel with sodium dodecyl sulfate and electrophoresed. The protein was then transferred to a PVDF membrane (Millipore, MA, USA). After blocking with 5% skim milk for 2 hours at room temperature, the primary antibody was incubated for an entire night at 4°C. After 1-hour incubation with a secondary antibody, exposure imaging with a molecular imaging system (Qinxiang Scientific Instruments Co., Ltd., Shanghai, China) was performed the next day. Image J (National Institutes of Health, USA) was used to examine the outcomes.

2.10. Apoptosis assay

Cells were seeded into 6-well plates and incubated for 48 hours with a drug-containing medium when the cell confluency reached 70%. Then, 1 × 106 cells were collected and stained according to the steps of the apoptosis kit instructions, and the percentage of apoptotic cells was determined using a FACSscan flow cytometer (Becton-Dickinson, NJ, USA).

2.11. Wound healing assay

On 6-well plates, cells were sown to reach the monolayer. A linear wound was formed by scraping with a 200 µL micropipette tip, and the cells were treated with morusin for 48 hours. The cell scratch area was observed with a microscope objective and photographed. And the degree of wound healing area was measured and calculated by Image J software to assess the cell migration rate.

2.12. Transwell migration assay

The lower chamber of the transwell was filled with the drug-containing medium (20% serum), and the upper chamber was filled with cell suspensions containing the same amount of morusin as the lower chamber. The cells which were seeded on the upper chamber were grown with a serum-free medium. After 48 hours, throw away the upper chamber medium and used a cotton swab to clean the remaining cells there. The chambers were first immersed in paraformaldehyde for 25 minutes, dyed for 15 minutes with a solution of 1% crystalline violet, and then cleaned 3 times with PBS. After drying, the chambers were examined under a microscope and captured on camera. Finally, the staining solution was removed from the chambers using 30% acetic acid, and the absorbance was detected at the 570 nm wavelength to assess the cell migration rate.

2.13. Statistical analysis

Statistical analysis was performed using GraphPad Prism 9.0 (CA, USA) and all experiments were repeated at least 3 times. Measured data are expressed as the means ± standard deviation. P values < 0.05 were considered statistically significant.

2.14. Ethical statement

This study does not include studies of human subjects, human data, or human tissues or animals. All data is obtained from the database, so ethical certification is not required.

3. Results

3.1. Screening potential targets of morusin for breast cancer based on network pharmacological analysis

From PharmMapper and Swiss Target Prediction databases, the possible targets for morusin were obtained. The GeneCards database was used to gather data on all human genes that have been annotated or are expected to cause breast cancer. Targets having a high degree of correlation with the disease were then evaluated and sorted by score. The intersection of 705 breast cancer-related targets and 367 putative morusin targets yielded a total of 101 intersected targets that may be important to morusin for the treatment of breast cancer (Fig. 1A). Via obtaining protein interaction prediction results from the STRING database, a PPI network by Cytoscape (Fig. 1B) was gained. Each node represents a target protein and the connecting lines show that there is an interaction between the 2 proteins. The nodes in the inner circle represent important target proteins. And the larger the node, the more significant the protein is. According to the PPI data, there are 106 total nodes, 602 predicted edges, 1802 actual edges, 34 average node degrees, and a clustering coefficient of 0.666 on average. This indicates that certain molecules interact more frequently. Through further analysis, some essential genes were discovered. The top 20 important targets, including ESR1, EGFR, ALB, CTNNB1, AKT1, HRAS, MAPK3, CASP3, ERBB2, HSP90AA1, SRC, IGF1, MMP9, PTGS2, AR, PGR, PIK3CA, MTOR, and MAPK1. These targets might be crucial in breast cancer treatment.

Figure 1.

Figure 1.

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Differential gene. (A) Gene targets of morusin and breast cancer. (B) Interaction network of targets for morusin against breast cancer.

3.2. GO and KEGG enrichment analysis

A total of 595 BPs, 71 cellular components, 120 MFs, and 157 signaling pathways were involved in the morusin treatment of breast cancer through DAVID analysis. The BPs are primarily related to apoptosis, migration, and proliferation, protein phosphorylation, as illustrated in Figure 2A. The most abundant cellular elements were the cytoplasm, receptor complex, cytoplasm, nucleoplasm, nucleus, extracellular area, and mitochondria (Fig. 2B). ATP binding, enzyme binding, protein serine/threonine kinase activity, and protein tyrosine kinase activity are the key MFs (Fig. 2C). Cancer pathways, prostate cancer, cancer proteoglycans, and PI3K-Akt signaling pathways were the most highly enriched in the KEGG pathway (Fig. 2D). And the PI3K-AKT signaling pathway was the top-ranked signaling pathway in the KEGG enrichment analysis. So, morusin may have a good antibreast cancer effect and may exercise its anticancer activity through the PI3K-Akt signaling pathway.

Figure 2.

Figure 2.

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Top 20 GO enrichment and KEGG pathway analysis histograms and scatter plots of the key targets of morusin and breast cancer. (A) Biological processes (BPs). (B) Cellular components (CCs). (C) Molecular functions (MFs). (D) KEGG. GO = Gene Ontology, KEGG = Kyoto Encyclopedia of Genes and Genomes.

3.3. Molecular docking

To demonstrate the biological activity of morusin, the binding of morusin to expected critical targets in the PI3K-AKT signaling was evaluated by molecular docking. Morusin was docked with PIK3CA and AKT1 (Fig. 3). The right side depicts a partial view of the docking, while the left side displays the entire docking results. The proline residue at position 108, the aspartate residue at position 154, and the valine residue at position 156 of PIK3CA all make hydrogen bonds with the small molecule, respectively. The molecule also established hydrogen bonds with AKT1’s threonine residue at position 211 and the asparagine residue at position 53. These docking results indicated that morusin binds to the targets by hydrogen bonding. Table 1 contains precise information about each protein, including its name, PDB ID, active center location, and docking binding energy. The binding energy between morusin and AKT1 is −7.03 kcal/mol, while the binding energy between morusin and PIK3CA is −7.7 kcal/mol (Table 1). When the binding energy is <0, there is a docking between morusin and protein, and if the binding energy is <−1.2, there has been satisfactory docking. Based on the binding result, morusin has a high affinity for PIK3CA and AKT1. In a word, the outcomes of GO and KEGG are further supported by molecular docking, and morusin likely exerts its anticancer effect via the PI3K-AKT signaling pathway.

Figure 3.

Figure 3.

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Interactions between morusin and receptor molecules. (A) Molecular docking model of morusin and PIK3CA. (B) Molecular docking model of morusin and AKT1.

Table 1.

The binding energy between morusin and the key targets.

Protein name PDB ID 3-dimensional coordinates of the active site Binding energy (kcal·mol−1)
PIK3CA 7RRG x = 40.107; y = −7.116; z = 21.662 −7.03
AKT1 7NH5 x = 13.935; y = −11.945; z = −15.594 −7.7
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3.4. Effects of morusin treatment on proliferation of breast cancer cells

To confirm the aforementioned assumption that morusin affects the proliferation of breast cancer, the CCK8 test was used. Figure 4 shows the 48-hour morusin therapy decreased the viability of breast cancer cells. The IC50 of MDA-MB-231, BT549, and Hs578T cells was 41.64 µmol/L, 21.31 µmol/L, and 12.44 µmol/L, respectively, whereas the IC50 of MCF-7, SK-BR-3, and T47D cells was 6.271 µmol/L, 5.219 µmol/L, and 40.47 µmol/L. Triple-negative (ER−, PR−, the human epidermal growth factor receptor 2 [Her2−]) breast cancer cells include MDA-MB-231, BT549, and Hs578T cells. MCF-7 (ER+, PR+, Her2−), SK-BR-3 (ER−, PR−, Her2+), and T47D (ER+, PR+, Her2−) are not triple-negative breast cancer cells. According to the findings, either triple-negative or non-triple-negative breast cancer cells are inhibited by morusin. With higher drug concentrations, stronger inhibition was seen. The 3 triple-negative breast cancer cells were used in the following research because their prognosis is less favorable than non-triple-negative breast cancer.

Figure 4.

Figure 4.

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Effect of the concentration of morusin on the viability of MDA-MB-231, BT549, Hs578T, MCF7, SK-BR-3, and T47D cells (CCK8). Data are given as mean ± SD of individual experiments with 3 plates in each experiment. SD = standard deviation.

3.5. Effect of morusin treatment on apoptosis of breast cancer cells

Using flow cytometry, the effect of morusin on cell apoptosis was tested. The apoptosis rates in MDA-MB-231 cells were 3.04% and 14.08%, respectively, in the control and morusin-treated groups (Fig. 5). Morusin dramatically accelerated MDA-MB-231 cells’ apoptosis. Additionally, following morusin treatment, the apoptosis rates of BT549 and Hs578T cells were 13.55% and 20.43%, respectively. Both groups treated with morusin had significantly higher apoptosis rates than the control group. These findings implied that morusin causes apoptosis in breast cancer cells and confirmed the network pharmacological results.

Figure 5.

Figure 5.

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Effect of morusin treatment of MDA-MB-231, BT549, and Hs578T cells on the apoptosis rate. (A) Representative pictures. (B) Statistical results. Data are given as mean ± SD of individual experiments with 3 plates in each experiment. **P < .01, vs control. SD = standard deviation.

3.6. Effects of morusin treatment on migration of breast cancer cells

Morusin has an impact on the migration of breast cancer cells, according to a bioinformatics investigation. The wound healing test also confirmed the results. The wound healing area of MDA-MB-231, BT549, and Hs578T cells were all reduced following morusin therapy compared to the control group (Fig. 6), and less area was healed as the concentration of morusin rose. Anyway, BT549, MDA-MB-231, and Hs578T cells’ migration was slowed down by morusin.

Figure 6.

Figure 6.

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Effect of morusin treatment of MDA-MB-231, BT549, and Hs578T cells on wound healing. (A) Representative pictures. (B) Statistical results. Data are given as mean ± SD of individual experiments with 3 plates in each experiment. *P < .05, **P < .01, vs control. SD = standard deviation.

Also, the transwell experiment confirmed the conclusions mentioned above. As depicted in Figure 7A, morusin treatment dramatically decreased the number of cells penetrating from the upper to the lower chamber, whereas the control group had the highest number of cells that go through the chamber (Fig. 7A). Morusin suppresses the migration of 3 breast cancer cells, according to the statistical findings as well (Fig. 7B). The experimental finding demonstrated that morusin has pharmacological efficacy in preventing MDA-MB-231, BT549, and Hs578T cells from migrating.

Figure 7.

Figure 7.

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Effect of morusin treatment of MDA-MB-231, BT549, and Hs578T cells on the migration (transwell assay). (A) Representative pictures. (B) Statistical results. Data are given as mean ± SD of individual experiments with 3 plates in each experiment. **P < .01, vs control. SD = standard deviation.

3.7. Effects of morusin treatment on PI3K/AKT signaling pathway in breast cancer cells

Using western blot, the phosphorylation state of PI3K and AKT as well as the expression level of the apoptosis marker cleaved-PARP were determined to further clarify whether morusin has anticancer effects through the PI3K-AKT signaling pathway. After 48 hours of morusin therapy, p-PI3K and p-AKT declined, while cleaved-PARP expression surged (Fig. 8). These results showed that morusin plays anticancer effects via the PI3K-AKT signaling pathway, and these results were consistent with network pharmacology and molecular docking analysis.

Figure 8.

Figure 8.

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Effect of morusin treatment of MDA-MB-231, BT549, and Hs578T cells on p-PI3K, PI3K, p-AKT, AKT, and cleaved-PARP expression.

4. Discussion

Breast cancer has become the most prevalent cancer type as a result of an increase in incidence. Breast carcinoma is categorized as hormone receptor-positive (ER/PR+, Her2−), Her2-positive (Her2+), and triple-negative (PR−, ER−, HER2−) based on the expression levels of estrogen receptors (ER), progesterone receptors (PR), and Her2.[15] Different programs are suggested depending on the molecular manifestation. Endocrine therapy and targeted therapy were administered to patients who were Her2-positive and hormone receptor-positive, respectively, while chemotherapy was preferred for triple-negative breast cancer patients.[3] However, the emergence of resistance has drastically decreased these regimens’ therapeutic efficacy.[16–18]

In numerous cancer research, morusin has been shown to inhibit the growth of hepatocellular carcinoma by AMPK-induced cycle arrest.[19] Morusin affects cell proliferation in colorectal cancer through signaling through the Akt/β-catenin pathway.[11] Additionally, it has substantial antitumor potential by regulating JNK, ERK, STAT3, and NFκB.[20–22] Because of the complexity of morusin, several investigations are needed to confirm the mechanism of therapeutic activity. Thus, we used bioinformatics which can streamline complicated processes to research the anticancer effect of morusin, forecast potential mechanisms and serve as the foundation and guide for subsequent in vitro or in vivo tests.

We discovered the top 20 essential targets through network interaction analysis, including ESR1, EGFR, ALB, CTNNB1, AKT1, HRAS, MAPK3, CASP3, ERBB2, HSP90AA1, SRC, IGF1, MMP9, PTGS2, AR, PGR, PIK3CA, MTOR, and MAPK1. In hormone receptor-positive breast tumors, the expression of the PR (PGR) and the estrogen receptor (ESR1) is enhanced, and both receptors are crucial to the tumors’ ability to migration.[23,24] And androgen receptor levels can be used to predict prognosis.[25] All of the transmembrane glycoproteins that bind to the epidermal growth factor and are encoded by Her2 (EGFR, ERBB2/Her2) are members of the ErbB protein family. Angiogenesis and the cell cycle are 2 BPs that are supported by the long-term activation of the ErbB protein family in cancer.[26,27] Her2 is a significant marker for staging breast cancer. Targeted therapies are typically used to treat breast cancer subtypes with elevated Her2 expression; however, side effects and the emergence of drug resistance decrease the efficacy of the therapy. The exploitability of morusin is suggested by the CCK8 experiment because morusin significantly inhibited SK-BR-3 (Her2+) cells (Fig. 4). In combination with E-cadherin and other proteins, the β-catenin protein, which is encoded by CTNNB1, works to maintain intercellular adhesion and hinder cell migration.[28] The proteins that AKT1 and PIK3CA encode are significant isoforms of AKT and PI3K, essential molecules in typical signaling pathways. One of the most significant mechanisms for cell proliferation and survival is the PI3K-AKT signaling system.[29,30] And other targets are all relevant to cell migration or proliferation.[31–36] To sum up, all of the top important genes discovered by PPI network interaction have a tight connection to cancer progression.

According to the results of the GO analysis, morusin is primarily involved in BPs like apoptosis, migration regulation, protein phosphorylation, and signal transduction, among others. These processes are closely related to the majority of the important genes discovered through PPI network interaction. The ability to invade and migrate is a key sign of cancer metastasis, and apoptosis is one of the most significant methods of cell death. Morusin was also shown by our in vitro experiment results to impede cell migration in addition to promoting cell death (Figs. 5–7). Additionally, we identified the expression of cleaved-PARP which is a biomarker of cell apoptosis, and the experimental outcomes also corroborated the data mentioned above (Fig. 8). The analysis of the KEGG pathway predicts specific key signal pathways. Among them, the PI3K-AKT signal pathway ranks first (Fig. 3). Through in vitro models, we further proved that morusin did quash the PI3K-AKT signal pathway (Fig. 8). These results suggest that morusin has a significant benefit in the treatment of breast cancer.

The top 20 signal pathways in KEGG, however, also contain the MAPK, Rap1, HIF-1, and other signal pathways. MAPK governs cell proliferation, differentiation, and death.[37–39] Cell migration is also regulated by Rap1. Through the use of integrins and adhesion molecules, the Rap1 signal pathway mediates interactions between cells and the cell matrix, and it is crucial for cell adhesion and intercellular junction.[40–43] Stable HIF-1 expression encourages glycolysis, invasion transfer, and the emergence of resistance by activating the HIF-1 signal pathway.[44–47] This implies that alternative targets and pathways may also be activated by morusin. Therefore, further exploration of the role and mechanism of morusin may yield more surprising findings.

5. Conclusion

In this study, network pharmacology and molecular docking technologies were used for the first time to determine the anticancer activity of morusin in breast cancer. Morusin triggered cell apoptosis and hindered cell migration via the PI3K-AKT signaling pathway. Therefore, the use of morusin in the treatment of breast cancer is promising, and this study provides a new direction for breast cancer treatment.

Author contributions

Data curation: Xue Li.

Funding acquisition: Qing Zhang.

Supervision: Jianlei Xiao, Qing Zhang.

Validation: Hangzhen Li, Xue Li, Qian Huang, Qingfeng Liu.

Writing – original draft: Qian Huang, Qingfeng Liu.

Writing – review & editing: Jianlei Xiao.

Abbreviations:

BP
biological process
ER
estrogen receptors
GO
Gene Ontology
Her2
the human epidermal growth factor receptor 2
KEGG
Kyoto Encyclopedia of Genes and Genomes
MF
molecular function
PPI
protein-protein interaction
PR
progesterone receptors

This work was supported by the Education and Teaching Reform Research Project of Southwest Medical University under Grant [JG201903]; Southwest Medical University Research Project Foundation under Grant [2020ZRQNB067]; Innovation Project of Science and Technology Department of Sichuan Province under Grant [22CXZX0153]; and Luzhou Health Social Work Project under Grant [JK-2022-52].

The authors have no conflicts of interest to disclose.

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

How to cite this article: Li H, Xiao J, Li X, Huang Q, Liu Q, Zhang Q. Mechanism of morusin on breast cancer via network pharmacology and in vitro experiments. Medicine 2023;102:28(e34300).

Contributor Information

Hangzhen Li, Email: 15908268535@163.com.

Jianlei Xiao, Email: magicwooder@swmu.edu.cn.

Xue Li, Email: 15908268535@163.com.

Qian Huang, Email: 593645726@qq.com.

Qingfeng Liu, Email: liuqingfeng_ok@126.com.

References

  • [1].Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71:209–49. [DOI] [PubMed] [Google Scholar]
  • [2].Arnold M, Morgan E, Rumgay H, et al. Current and future burden of breast cancer: Global statistics for 2020 and 2040. Breast. 2022;66:15–23. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [3].Waks AG, Winer EP. Breast cancer treatment: a review. JAMA. 2019;321:288–300. [DOI] [PubMed] [Google Scholar]
  • [4].Masoud V, Pages G. Targeted therapies in breast cancer: new challenges to fight against resistance. World J Clin Oncol. 2017;8:120–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [5].Okada F. Kampo medicine, a source of drugs waiting to be exploited. Lancet. 1996;348:5–6. [DOI] [PubMed] [Google Scholar]
  • [6].Xu Q, Bauer R, Hendry BM, et al. The quest for modernisation of traditional Chinese medicine. BMC Complement Altern Med. 2013;13:132. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [7].Jia Y, He W, Zhang H, et al. Morusin ameliorates IL-1beta-Induced chondrocyte inflammation and osteoarthritis via NF-kappaB signal pathway. Drug Des Devel Ther. 2020;14:1227–40. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [8].Kim TI, Kwon EB, Oh YC, et al. Mori ramulus and its major component morusin inhibit herpes simplex virus type 1 replication and the virus-induced reactive oxygen species. Am J Chin Med. 2021;49:163–79. [DOI] [PubMed] [Google Scholar]
  • [9].Pang D, Liao S, Wang W, et al. Destruction of the cell membrane and inhibition of cell phosphatidic acid biosynthesis in Staphylococcus aureus: an explanation for the antibacterial mechanism of morusin. Food Funct. 2019;10:6438–46. [DOI] [PubMed] [Google Scholar]
  • [10].Park HJ, Min TR, Chi GY, et al. Induction of apoptosis by morusin in human non-small cell lung cancer cells by suppression of EGFR/STAT3 activation. Biochem Biophys Res Commun. 2018;505:194–200. [DOI] [PubMed] [Google Scholar]
  • [11].Zhou Y, Li X, Ye M. Morusin inhibits the growth of human colorectal cancer HCT116-derived sphere-forming cells via the inactivation of Akt pathway. Int J Mol Med. 2021;47:1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [12].Hopkins AL. Network pharmacology. Nat Biotechnol. 2007;25:1110–1. [DOI] [PubMed] [Google Scholar]
  • [13].Li FS, Weng JK. Demystifying traditional herbal medicine with modern approach. Nat Plants. 2017;3:17109. [DOI] [PubMed] [Google Scholar]
  • [14].Yildirim MA, Goh KI, Cusick ME, et al. Drug-target network. Nat Biotechnol. 2007;25:1119–26. [DOI] [PubMed] [Google Scholar]
  • [15].Falato C, Schettini F, Pascual T, et al. Clinical implications of the intrinsic molecular subtypes in hormone receptor-positive and HER2-negative metastatic breast cancer. Cancer Treat Rev. 2023;112:102496. [DOI] [PubMed] [Google Scholar]
  • [16].Famta P, Shah S, Jain N, et al. Tumor-promoting aftermath post-chemotherapy: a focus on breast cancer. Life Sci. 2022;310:121125. [DOI] [PubMed] [Google Scholar]
  • [17].Osborne CK, Schiff R. Mechanisms of endocrine resistance in breast cancer. Annu Rev Med. 2011;62:233–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [18].Wilks ST. Potential of overcoming resistance to HER2-targeted therapies through the PI3K/Akt/mTOR pathway. Breast. 2015;24:548–55. [DOI] [PubMed] [Google Scholar]
  • [19].Cho AR, Park WY, Lee HJ, et al. Antitumor effect of morusin via G1 arrest and antiglycolysis by AMPK activation in hepatocellular cancer. Int J Mol Sci . 2021;22. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [20].Huang CC, Wang PH, Lu YT, et al. Morusin suppresses cancer cell invasion and MMP-2 expression through ERK signaling in human nasopharyngeal carcinoma. Molecules. 2020;25:4851. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [21].Lin WL, Lai DY, Lee YJ, et al. Antitumor progression potential of morusin suppressing STAT3 and NFkappaB in human hepatoma SK-Hep1 cells. Toxicol Lett. 2015;232:490–8. [DOI] [PubMed] [Google Scholar]
  • [22].Wang J, Liu X, Zheng H, et al. Morusin induces apoptosis and autophagy via JNK, ERK and PI3K/Akt signaling in human lung carcinoma cells. Chem Biol Interact. 2020;331:109279. [DOI] [PubMed] [Google Scholar]
  • [23].Grinshpun A, Sandusky ZM, Jeselsohn R. The clinical utility of ESR1 mutations in hormone receptor-positive, HER2-negative advanced breast cancer. Hematol Oncol Clin North Am. 2023;37:169–81. [DOI] [PubMed] [Google Scholar]
  • [24].Intrieri T, Manneschi G, Caldarella A. 10-year survival in female breast cancer patients according to ER, PR and HER2 expression: a cancer registry population-based analysis. J Cancer Res Clin Oncol. 2022. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [25].Tagliaferri B, Quaquarini E, Palumbo R, et al. Role of androgen receptor expression in early stage ER+/PgR-/HER2- breast cancer. Ther Adv Med Oncol. 2020;12:1758835920958355. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [26].Kaler AK, Patel K, Patil H, et al. Mutational analysis of EGFR mutations in non-small cell lung carcinoma – an Indian perspective of 212 patients. Int J Environ Res Public Health. 2022;20:758. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [27].Wee P, Wang Z. Epidermal growth factor receptor cell proliferation signaling pathways. Cancers (Basel). 2017;9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [28].Li X, Yang J, Ni R, et al. Hypoxia-induced lncRNA RBM5-AS1 promotes tumorigenesis via activating Wnt/beta-catenin signaling in breast cancer. Cell Death Dis. 2022;13:95. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [29].Pascual J, Turner NC. Targeting the PI3-kinase pathway in triple-negative breast cancer. Ann Oncol. 2019;30:1051–60. [DOI] [PubMed] [Google Scholar]
  • [30].Hinz N, Jucker M. Distinct functions of AKT isoforms in breast cancer: a comprehensive review. Cell Commun Signal. 2019;17:154. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [31].Guo YJ, Pan WW, Liu SB, et al. ERK/MAPK signalling pathway and tumorigenesis. Exp Ther Med. 2020;19:1997–2007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [32].Prior IA, Hood FE, Hartley JL. The frequency of Ras mutations in cancer. Cancer Res. 2020;80:2969–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [33].Schexnayder C, Broussard K, Onuaguluchi D, et al. Metformin inhibits migration and invasion by suppressing ROS production and COX2 expression in MDA-MB-231 breast cancer cells. Int J Mol Sci . 2018;19. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [34].Sundararajan R, Giri P, Madhivanan S, et al. Cisplatin-based electrochemotherapy significantly downregulates key heat shock proteins in MDA-MB-231-human triple-negative breast cancer cells. Appl Biochem Biotechnol. 2022;194:517–28. [DOI] [PubMed] [Google Scholar]
  • [35].Pelaz SG, Tabernero A. Src: coordinating metabolism in cancer. Oncogene. 2022;41:4917–28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [36].Cerma K, Piacentini F, Moscetti L, et al. Targeting PI3K/AKT/mTOR pathway in breast cancer: from biology to clinical challenges. Biomedicines. 2023;11:109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [37].Xie SY, Shi DB, Ouyang Y, et al. SHMT2 promotes tumor growth through VEGF and MAPK signaling pathway in breast cancer. Am J Cancer Res. 2022;12:3405–21. [PMC free article] [PubMed] [Google Scholar]
  • [38].Zhao Y, Fu L, Chen J, et al. Eupalinolide O induces apoptosis in human triple-negative breast cancer cells via modulating ROS generation and Akt/p38 MAPK signaling pathway. J Oncol. 2022;2022:8802453. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [39].Lee S, Rauch J, Kolch W. Targeting MAPK signaling in cancer: mechanisms of drug resistance and sensitivity. Int J Mol Sci . 2020;21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [40].Kooistra MR, Dube N, Bos JL. Rap1: a key regulator in cell-cell junction formation. J Cell Sci. 2007;120(Pt 1):17–22. [DOI] [PubMed] [Google Scholar]
  • [41].Sawant K, Chen Y, Kotian N, et al. Rap1 GTPase promotes coordinated collective cell migration in vivo. Mol Biol Cell. 2018;29:2656–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [42].Zhang YL, Wang RC, Cheng K, et al. Roles of Rap1 signaling in tumor cell migration and invasion. Cancer Biol Med. 2017;14:90–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [43].Retta SF, Balzac F, Avolio M. Rap1: a turnabout for the crosstalk between cadherins and integrins. Eur J Cell Biol. 2006;85:283–93. [DOI] [PubMed] [Google Scholar]
  • [44].Assidicky R, Tokat UM, Tarman IO, et al. Targeting HIF1-alpha/miR-326/ITGA5 axis potentiates chemotherapy response in triple-negative breast cancer. Breast Cancer Res Treat. 2022;193:331–48. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [45].Chen G, Wu K, Li H, et al. Role of hypoxia in the tumor microenvironment and targeted therapy. Front Oncol. 2022;12:961637. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [46].Niu Z, Fan J, Chen F, et al. RBCK1 regulates the progression of ER-positive breast cancer through the HIF1alpha signaling. Cell Death Dis. 2022;13:1023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • [47].Yang H, Geng YH, Wang P, et al. Extracellular ATP promotes breast cancer chemoresistance via HIF-1alpha signaling. Cell Death Dis. 2022;13:199. [DOI] [PMC free article] [PubMed] [Google Scholar]

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