Skip to main content
Download PDF

Essential oils from Amorpha fruticosa against hepatocellular carcinoma based on network pharmacology

BMC Complementary Medicine and Therapies volume 25, Article number: 29 (2025) Cite this article

Abstract

Background

Amorpha fruticosa was used for treating burn, ambustion, carbuncle, and eczema in the traditional Chinese medicine. Although more and more attention has been paid to its biological activity recently, the antitumor activities of the essential oils (EOs) extracted from its leaves (AFLEO) and flowers (AFFEO), and their molecular mechanisms have never been reported up to now. The objective of present study was to examine the chemical compositions of AFLEO and AFFEO, then investigate the effects and pharmacological mechanism of EOs against hepatocellular carcinoma (HCC).

Methods

The chemical compositions of EOs were examined using gas chromatography-mass spectrometry (GC-MS). The inhibitory effect of the EOs on HCC was evaluated by MTT assay. The detected components of AFLEO and AFFEO were performed ADME screening to examine their drug-likeness. Then a PPI network, compound-target network, compound-target-pathway network, gene ontology, and KEGG enrichment for HCC were applied to identify the targets and pathways for AFLEO and AFFEO against HCC. Molecular docking of the main components and their targets was performed to predict the binding affinity. Western blotting was used to verify the results.

Results

30 components were identified from AFLEO, while 22 components from AFFEO. Both AFLEO and AFFEO inhibited the proliferation of HCC cells in a time and dose-dependent manner. 10 compounds of AFLEO and 9 compounds of AFFEO were screened out for further analysis. 28 hub targets of AFLEO and 40 hub targets of AFFEO were detected by PPI network. KEGG analysis revealed that pathways in cancer, chemical carcinogenesis - receptor activation and proteoglycans in cancer were related to the EOs against HCC. Molecular docking confirmed that the main component of the EOs has high affinity to the targets of HCC.

Conclusions

AFLEO and AFFEO may suppress HCC by acting on multiple targets and regulating multiple pathways.

Peer Review reports

Background

Hepatocellular carcinoma (HCC) is one of the most malignant and lethal cancers in the world. The most common cause of HCC is chronic viral infection, with about 80% of HCC cases attributed to chronic infection with hepatitis B and hepatitis C [1]. Currently, the clinically treatment strategies for HCC include surgery, chemotherapy, radiation therapy, molecular targeted therapy or their combination. Among them, chemotherapy is the standard treatment method for the advanced HCC [2]. However, due to the adverse reactions and drug resistance, the prognosis of HCC is still poor, and the five-year survival rate is only 18% [3]. In addition to the traditional malignant tumor treatments, exploring more effective and lower toxicity antitumor chemicals has become an important issue in the field of HCC diagnosis and treatment research.

Amorpha fruticosa L., which belongs to the genus Amorpha in Leguminosae family, contains flavonoids [4,5,6], stilbene glycosides [7], essential oil [8] and other chemical components. In the traditional Chinese medicine, Amorpha fruticosa was used for treating burn, ambustion, carbuncle, and eczema [9]. In recent years, more and more attention has been paid to its biological activity. Pharmacological research has demonstrated that the extracts of Amorpha fruticosa have potential medicinal values in anti-tumor [10,11,12], anti-inflammatory [13], liver protection [14] and antibacterial [5]. However, the research on the pharmacological activity of Amorpha fruticosa mainly focus on flavonoids. There is little literature on the compositions of the essential oils (EOs) extracted from the leaves (AFLEO) and flowers (AFFEO) of Amorpha fruticose [15], and the reported constituents are significantly different from what we detected possibly for the difference in geographical location. To the best of our knowledge, the antitumor activities of AFLEO and AFFEO and their molecular mechanisms have never been reported up to now.

In the present study, the fresh leaves and flowers of Amorpha fruticosa were collected first. Then the EOs of Amorpha fruticosa were prepared to identify their chemical compositions and antitumor activity. In addition, network pharmacology was used to predict potential processes and elucidate the molecular mechanisms for EOs of Amorpha fruticosa against HCC.

Materials and methods

Plant material

The fresh leaves and flowers of Amorpha fruticosa were purchased from Mingquan Amorpha fruticosa culture base, Henan Province of China in June 2021. The leaves and flowers were washed and air-dried at room temperature for 1 week.

Preparation of the essential oil

Air-dried Amorpha fruticosa leaves and flowers were crushed into powders. Approximately 150 g of each sample was submitted to hydrodistillation in a Clevenger-type apparatus at 100 ℃ for 5 h. The obtained EOs were extracted by ether and dried with anhydrous sodium sulfate. After filtration, pure oils were stored at 4℃ in dark.

Gas Chromatograph-Mass Spectrometry (GC-MS) analysis

The composition of EOs were identified by using an Agilent 7890 A gas chromatograph equipped with a HP-5MS fused silica capillary tubes column (30 m×250 μm×0.25 μm) connected to a 5975 C mass spectrometer (Agilent, Palo Alto, CA, U.S.A.). The carrier gas was Helium (purity > 99.999%) and the flow rate was 1 ml/min. The sample was diluted by hexane. The injection volume was 1 µl, and the split less mode was used. Temperature program was as follows: initial temperature of 40 ℃ for 5 min, increased 2.5 ℃/min up to 65 ℃ and held for 1 min. Then the temperature was raised to 200 ℃ at 8 °C/min and kept at that temperature for 2 min, finally increased to 250 ℃ at 10 °C/min, and maintained for 2 min. The injector and ion source temperature were 250 ℃ and 230 ℃. The ionization voltage was 70 eV, and the mass scan range 33–400 Da was used. Each component was identified according to its retention indices and mass spectra. Retention indices were calculated using a homologous series of C8-C20 n-alkanes injected under the same experimental conditions. Mass spectra were compared with the corresponding standard spectra in National Institute of Standards and Technology (NIST) library. The relative peak area of the components was calculated using the normalization method.

MTT assay

The Huh7 and HepG2 cells were cultured in DMEM medium supplemented with 10% FBS at 37℃ with a humid atmosphere containing 5% CO2. To perform MTT assay, Huh7 and HepG2 cells were seeded into a 96-well plate and for 48 h after treating with different concentrations of AFLEO and AFFEO (20, 50, 100, 200, 500 and 1000 µg/mL), respectively. Then, the cells were added 20 µl MTT and incubated for 4 h. After that, 100 µl of DMSO was added to dissolve the crystal, and the absorbance was measured at 490 nm by a microplate reader.

Identification of active ingredients and prediction of targets of AFLEO and AFFEO

SwissADME (http://www.swissadme.ch/) [16] was used to search for the active ingredients of AFLEO and AFFEO. An ingredient is considered to be active when it meets the conditions as follows: human gastrointestinal absorption (HIA) was “high”, blood-brain barrier (BBB) permeation was “yes”, and at least two models among five drug-likeness models (Lipinski, Ghose, Veber, Egan, and Muegge) were “yes”. Then SwissTargetPrediction database (http://www.swisstargetprediction.ch/) [17] was used to identify the protein targets of the active ingredients.

Protein targets related to HCC

To ensure comprehensive collection of genes associated with HCC, GeneCards (http://www.genecards.org/) [18] and DisGeNET (https://www.disgenet.org/) [19] were adopted to search for the HCC-related targets. Then the overlapping targets of AFLEO and HCC, as well as AFFEO and HCC, which were considered potential targets of AFLEO or AFFEO in the treatment of HCC, were identified by jvenn (https://jvenn.toulouse.inrae.fr/app/example.html) [20].

Construction of (protein–protein interaction) PPI Network

Direct and indirect interactions of the overlapping targets between AFLEO or AFFEO and HCC were identified by the Search Tool for the Retrieval of Interacting Genes (STRING) database (https://string-db.org/) [21]. The specie was “Homo sapiens” and the minimum required interaction score was 0.4. Then the PPI network was imported to Cytoscape 3.9.1 to evaluate its topological characteristics, including the degree, betweenness and closeness.

Gene Ontology (GO) and Kyoto Encyclopedia of genes and the genomes (KEGG) Enrichment analysis

GO and KEGG pathway enrichment analysis were performed using the Integrated Annotation and Discovery Visualization Database (DAVID) (https://david.ncifcrf.gov/) [22] and plotted by the online platform for data analysis and visualization (http://www.bioinformatics.com.cn/). GO functions and KEGG pathways with a p-value < 0.05 were considered as the main terms of clustering.

Network construction and analysis

The compound–target network and the compound–target–pathway network were constructed using Cytoscape 3.9.1 to analyze the complicated interconnection of compounds, targets and pathways.

Molecular docking

The 3D structure of nerolidol was obtained through the PubChem (https://pubchem.ncbi.nlm.nih.gov/). The Protein Data Bank (PDB, https://www.rcsb.org/) was used to obtain the 3D structures of its target proteins. Autodock vina (https://autodock.scripps.edu/) was used to dock active ingredients with target proteins. The binding energy less than − 5.0 kcal/mol was considered as tight binding.

Western blotting

After treated with AFLEO for 48 h, HCC cells were lysed in ice-cold RIPA lysis buffer (Leagene, China) for 30 min and then centrifuged for 10 min (12, 000 × g, 4 ℃). Protein concentration was detected using the BCA Quantitation Kit (Thermo Fisher Scientific, USA). 20 µg protein was run on 10% SDS-PAGE gel and transferred to polyvinylidene fluoride membranes (PVDF) (0.45 μm pore size, Millipore, USA). The membranes were blocked with 5% non-fat powdered milk for 2 h at 25 ℃. Then the membranes were incubated overnight at 4 ℃ with primary antibodies, including anti-GAPDH (1:10000, Proteintech, China), anti-AKT1 (1:1000, Cell Signaling Technology, USA), anti-PPARG (1:1000, Wanleibio, China), and anti-MAPK3 (1:1000, Abcam, USA), and then incubated with horseradish peroxidase (HRP)-conjugated goat anti-rabbit IgG (1:10000, Sangon Biotech, China) secondary antibody for 2 h at 25 ℃. The luminescence reaction was conducted with an ECL kit (Geneview, USA). GAPDH was used as internal control.

Statistical analysis

All the experiments were conducted independently in triplicate (n = 3). The data are expressed as the mean ± SD. All analyses were performed using Graphpad 6.0.

Results

Chemical composition of the EOs

Both AFLEO and AFFEO were light yellow color with special aroma. The yield (v/w) of them were 0.67% and 0.43%, respectively. The chemical components of EOs were identified by GC-MS. The chromatogram spectrum can be seen in Fig. S1. The results are shown in Table 1. 30 components were identified from AFLEO, and 22 components were identified from AFFEO. AFLEO consisted primarily of alcohols (51.49%), along with olefins (32.77%), ketones (1.46%), alkanes (2.92%), benzene (1.88%) and naphthalene (1.12%). The major components of AFLEO were nerolidol (11.7%), farnesol (6.73%) and phytol (6.63%). Similar to AFLEO, AFFEO was also abundant in alcohols (46.15%), olefins (28.75%), alkanes (9.73%), ketones (5.77%), benzene (3.42%) and naphthalene (1.89%). The major components of AFFEO were nerolidol (11.07%), farnesol (8.21%) and viridiforol (8.0%).

Table 1 Constituents of the essential oils
Full size table

Antitumor activity

Antitumor activities of AFLEO and AFFEO were determined by MTT assay. As seen in Fig. 1, both AFLEO and AFFEO inhibited the proliferation of Huh7 and HepG2 cells in a time and dose-dependent manner.

Fig. 1
figure 1

Effects of (A) AFLEO and (B) AFFEO on cell viability of Huh 7 and HepG2 cells. Each value represents as the mean ± SD (n = 3)

Full size image

Prediction of EOs targets and HCC targets

10 active ingredients of AFLEO and 9 of AFFEO were screened out according to the parameters of HIA, BBB permeation, and drug-likeness (Table S1 & S2). SwissTargetPrediction was used to obtain the potential targets of each ingredient. After removing the duplicate targets, 240 targets of AFLEO and 298 targets of AFFEO were obtained. Then a total of 8685 targets related to HCC were found by GeneCards and DisGeNET database. Venn diagrams were created to obtain the overlapping targets. As seen in Fig. 2, there were 176 AFLEO targets and 209 AFFEO targets that overlapped with HCC targets and were considered potential targets for AFLEO or AFFEO in treating HCC.

Fig. 2
figure 2

The Venn diagrams of the overlapping targets between HCC and (A) AFLEO and (B) AFFEO

Full size image

Construction and analysis of PPI Network

A PPI network was obtained after importing the overlapping targets into the STRING database. As shown in Fig. 3, for AFLEO, with closeness ≥ 0.002553852, betweenness ≥ 232.1169591 and degree ≥ 16.24561404, the PPI network with 28 nodes and 214 edges was obtained. The top 8 targets included AKT1, PPARG, EGFR, PTGS2, ESR1, HIF1A, MAPK3 and ERBB2. For AFFEO, with closeness ≥ 0.002136257, betweenness ≥ 275.1764706 and degree ≥ 17.5, the PPI network with 40 nodes and 348 edges was obtained. The top 8 targets included TNF, PPARG, EGFR, PTGS2, ESR1, HIF1A, MMP9 and GSK3B. Besides, the associations between these top 8 hub targets and HCC were assessed according to gifts in Genecards database. As shown in table S3, these hub targets were closely related to HCC.

Fig. 3
figure 3

(A) AFLEO and (B) AFFEO hub targets interactions in the PPI network

Full size image

The analysis of GO functions and KEGG pathway enrichment

GO functional analysis of the 175 targets of AFLEO and 208 targets of AFFEO against HCC were conducted to identify the functional role of them. As shown in Fig. 4A and B, the top 10 terms of BP, CC, and MF were ranked according to the p-value. The BP analysis revealed that the targets of AFLEO and AFFEO were mainly related to the protein phosphorylation, inflammatory response, and intracellular receptor signaling pathway. The CC analysis of AFLEO and AFFEO showed that the genes were highly enriched in cytoplasm, cytosol and plasma membrane. According to the MF, targets of AFLEO and AFFEO were mainly related to protein serine/threonine/tyrosine kinase activity, ligand-activated sequence-specific DNA binding, protein kinase activity and enzyme binding.

Fig. 4
figure 4

GO enrichment analysis of (A) AFLEO and (B) AFFEO; KEGG enrichment analysis of (C) AFLEO and (D) AFFEO

Full size image

The top 20 pathways of the KEGG enrichment analysis ranked according to the p-value were shown in Fig. 4C and D. The KEGG pathways of AFLEO and AFFEO against HCC were mainly related to pathways in cancer, Chemical carcinogenesis - receptor activation, inflammatory mediator regulation of TRP channels, proteoglycans in cancer and PD-L1 expression and PD-1 checkpoint pathway in cancer.

Construction of component-target network

The compound-target networks were constructed by the 29 key targets of AFLEO and 40 key targets of AFFEO obtained by topological analysis. As seen Fig. 5A and B, the network of AFLEO consisted of 39 nodes and 133 edges. While the network of AFFEO consisted of 51 nodes and 153 edges.

Fig. 5
figure 5

The compound-target network of (A) AFLEO and (B) AFFEO; The compound-target-pathway network of (C) AFLEO and (D) AFFEO

Full size image

The results of the compound-target-pathway network were demonstrated in Fig. 5C and D. The network of AFLEO consisted of 49 nodes and 203 edges. While the network of AFFEO consisted of 61 nodes and 229 edges. The results demonstrated that multiple components of AFLEO and AFFEO had multiple targets to treat HCC through various pathways.

Molecular docking analysis

As nerolidol is the most abundant component of both AFLEO and AFFEO, the overlapping targets of it and key protein targets of AFLEO and AFFEO were selected to do molecular docking. The binding energy of nerolidol and the protein target was shown in Table 2. Some docking results were visualized in Fig. 6.

Table 2 The binding energy between nerolidol and its targets
Full size table
Fig. 6
figure 6

Molecular docking showed the binding of Nerolidol to (A) NR1I2, (B) CYP2C9, (C) CYP3A4, (D) PTGS2, (E) PGR and (F) JAK2

Full size image

Validation of target proteins via Western blotting

To verify the target proteins obtained via the above network, western blotting was performed. As shown in Fig. 7, the expression of AKT1 and MAPK3 decreased, while the expression of PPARG increased in HCC cells. Therefore, western blotting confirmed the reliability of the network pharmacology results.

Fig. 7
figure 7

Western blot validation. AFLEO decreased the expression of (A) AKT1 and MAPK3 while increased the expression of (B) PPARG

Full size image

Discussion

EOs are mixtures extracted from plants. Many kinds of EOs have the effects of antibacterial, antioxidant, antiviral, anti-inflammatory and antitumor. The bioactivity of EOs is related to their compositions [23]. Many compounds of AFLEO and AFFEO have important known biological activities, such as nerolidol, α-bisabolol, β-eudesmol and caryophyllene oxide. Nerolidol and α-bisabolol have antibacterial, antitumor, anti-inflammatory and antioxidant activities [24,25,26]. β-Eudesmol and caryophyllene oxide have anticancer and anti-inflammatory effects [27,28,29,30]. Therefore, considering the active substances identified in AFLEO and AFFEO, the EOs should have antitumor effects. To confirm the antitumor activity of AFLEO and AFFEO, MTT assays were performed. The decreased cell viability of Huh7 and HepG2 proved that AFLEO and AFFEO inhibit the proliferation of HCC cells.

Except the diverse chemical compositions of EOs, the mechanism of their pharmacological action is also complex as they can influence biological processes at cellular levels by interacting with multiple biological targets [23]. The network pharmacology analysis combined with molecular docking method were applied to determine the mechanisms of AFLEO and AFFEO against HCC. As shown in PPI network, AFLEO had 28 hub targets, such as AKT1, PPARG, EGFR, PTGS2, ESR1, HIF1A, MAPK3 and ERBB2, whereas AFFEO has 40 hub targets, such as TNF, PPARG, EGFR, PTGS2, ESR1, HIF1A, MMP9 and GSK3B. Previous studies have revealed that those targets are closely related to cell proliferation, differentiation, apoptosis [31,32,33,34,35], metabolism [36, 37], and immune microenvironment, which are involved in the development of HCC [38,39,40,41].

GO enrichment analysis showed that the targets of both AFLEO and AFFEO were closely related to 3 biological processes, including protein phosphorylation, inflammatory response, and signal transduction. KEGG pathway enrichment analysis showed that the targets of both AFLEO and AFFEO against to HCC were mainly enriched in pathways in cancer, Chemical carcinogenesis - receptor activation, inflammatory mediator regulation of TRP channels, proteoglycans in cancer, EGFR tyrosine kinase inhibitor resistance, and in cancer. It is well known that phosphorylation is one important post translational modifications, which could regulate cell growth, differentiation, apoptosis and cell signaling. Dysregulation of protein phosphorylation may cause many serious diseases, especially cancer [42]. Chronic inflammation promotes tumor development, including HCC. Inflammatory tumor microenvironment may lead to the proliferation, angiogenesis and metastasis of malignant cells [43]. The activity of signaling pathways is always altered in tumor cells, which will influence growth, proliferation, apoptosis, invasiveness, and metastasis of the cells. From the KEGG results, several signaling pathways closely related to HCC were enriched, such as VEGF signaling pathway and Ras signaling pathway. The result of KEGG showed that inflammatory mediator regulation of TRP channels may be an important pathway for both AFLEO and AFFEO in treating HCC. The association between TRP channels and cardiovascular diseases has been widely studied. However, more and more research found that TRP channels also play crucial roles in tumorigenesis and progression. Dysregulated TRP channel expression promotes cell proliferation, promote migration and invasion [44], protect cells from apoptosis through hypoxia [45], elevated oxidative stress and abnormal redox [46]. TRP channel also affects cancer progression by influence the immunocytes and tumor microenvironment [47]. We also noticed that the targets were also enriched into PD-L1 expression and PD-1 checkpoint pathway in cancer, which is related to T cell immunity. As the key targets, AKT1 is involved in VEGF signaling pathway and HIF-1 signaling pathway, MAPK3 is involved in Ras signaling pathway, while PPARG is involved in insulin resistance pathway. The result of GO and KEGG analysis indicated that AFLEO and AFFEO not only act directly on the tumor cells, but also affect the tumor microenvironment.

The binding ability between nerolidol and the key targets of AFLEO and AFFEO was detected by the molecular docking method. The binding energy between the receptor and ligand was lower than − 5 kcal/mol, which indicated that nerolidol and its targets may play a key role in the treatment of HCC. Among these targets, NR1I2, CYP2C9, CYP3A4, PTGS2, PGR, and JAK2 have higher binding energy. NR1I2, CYP2C9 and CYP3A4 are important regulators of hepatocellular carcinoma cellular resistance to antitumor drugs [48,49,50]. PTGS2 and JAK2 are related to proliferation, invasion, metastasis, and apoptosis of hepatocellular carcinoma cells [33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51]. PGR is associated with abnormal epigenetic silencing mechanisms in HCC cells [52]. However, the results of network pharmacology and molecular docking were only preliminary, and current results did not fully indicate whether AFLEO and AFFEO could be applied to HCC treatment. Further in vivo and in vitro experiments are needed to verify the active ingredients, targets and pathways of AFLEO and AFFEO against HCC.

Conclusions

The components of AFLEO and AFFEO were analyzed by GC-MS. A total of 30 and 22 compounds were identified in AFLEO and AFFEO, respectively. Nerolidol was the most abundant component of both essential oils. Both AFLEO and AFFEO can inhibit the proliferation of HCC. AFLEO and AFFEO may exert their antitumor effect by regulating multiple targets, such as PPARG, EGFR, PTGS2, ESR1 and HIF1A. Moreover, their therapeutic effects may relate to multiple pathways. Therefore, AFLEO and AFFEO have the potential to be studied and developed as candidate drugs for HCC treatment.

Data availability

All the data are included in the article and supplementary material, further inquiries can be directed to the corresponding authors.

Abbreviations

AFLEO:

Essential oil extracted from Amorpha fruticosa leaves

AFFEO:

Essential oil extracted from Amorpha fruticosa flowers

EOs:

Essential oils

GC-MS:

Gas chromatography-mass spectrometry

HCC:

Hepatocellular carcinoma

NIST:

National Institute of Standards and Technology

HIA:

Human gastrointestinal absorption

BBB:

Blood-brain barrier

PPI:

Protein–protein interaction

STRING:

Search Tool for the Retrieval of Interacting Genes

GO:

Gene Ontology

KEGG:

Kyoto Encyclopedia of Genes and the Genomes

DAVID:

Integrated Annotation and Discovery Visualization Database

References

  1. de Martel C, Maucort-Boulch D, Plummer M, Franceschi S. World-wide relative contribution of hepatitis B and C viruses in hepatocellular carcinoma. Hepatology. 2015;62(4):1190–200.

    Article  PubMed  Google Scholar 

  2. Lau WY, Ho SK, Yu SC, Lai EC, Liew CT, Leung TW. Salvage surgery following downstaging of unresectable hepatocellular carcinoma. Ann Surg. 2004;240(2):299–305.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Altekruse SF, McGlynn KA, Dickie LA, Kleiner DE. Hepatocellular carcinoma confirmation, treatment, and survival in surveillance, epidemiology, and end results registries, 1992–2008. Hepatology. 2012;55(2):476–82.

    Article  PubMed  Google Scholar 

  4. Somleva T, Ognyanov I. New rotenoids in Amorpha fruticosa fruits. Planta Med. 1985;51(3):219–21.

    Article  Google Scholar 

  5. Masayoshi O, Toshiyuki T, Munekazu I. A prenylated flavanone from roots of Amorpha fruticosa. Phytochemistry. 1998;48(5):907–9.

    Article  Google Scholar 

  6. Kim YS, Ryu YB, Curtis-Long MJ, Yuk HJ, Cho JK, Kim JY, Kim KD, Lee WS, Park KH. Flavanones and rotenoids from the roots of Amorpha fruticosa L. that inhibit bacterial neuraminidase. Food Chem Toxicol. 2011;49(8):1849–56.

    Article  CAS  PubMed  Google Scholar 

  7. Kemal M, Wahba Khalil SK, Rao NG, Woolsey NF. Isolation and identification of a cannabinoid-like compound from Amorpha species. J Nat Prod. 1979;42(5):463–8.

    Article  CAS  PubMed  Google Scholar 

  8. Stoyanova A, Georgiev E, Lis A, Majda T, Gora J. Essential oil from stored fruits of Amorpha fruticosa L. J Essent Oil Bearing Plants. 2003;6(3):195–7.

    Article  CAS  Google Scholar 

  9. Das PK, Goswami S, Chinniah A, Panda N, Banerjee S, Sahu NP, Achari B. Woodfordia fruticosa: traditional uses and recent findings. J Ethnopharmacol. 2007;110(2):189–99.

    Article  CAS  PubMed  Google Scholar 

  10. Li L, Wang HK, Chang JJ, et al. Antitumor agents, 138. Rotenoids and isoflavones as cytotoxic constitutents from Amorpha fruticosa. J Nat Prod. 1993;56(5):690–8.

    Article  CAS  PubMed  Google Scholar 

  11. Dat NT, Lee JH, Lee K, Hong YS, Kim YH, Lee JJ. Phenolic constituents of Amorpha fruticosa that inhibit NF-kappaB activation and related gene expression. J Nat Prod. 2008;71(10):1696–700.

    Article  PubMed  Google Scholar 

  12. Choi Y, Lee JH. The combination of tephrosin with 2-deoxy-D-glucose enhances the cytotoxicity via accelerating ATP depletion and blunting autophagy in human cancer cells. Cancer Biol Ther. 2011;12(11):989–96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Fuhr L, Rousseau M, Plauth A, Schroeder FC, Sauer S. Amorfrutins are natural PPARγ agonists with potent anti-inflammatory properties. J Nat Prod. 2015;78(5):1160–4.

    Article  CAS  PubMed  Google Scholar 

  14. Kloutek E, Popov A, Drenska D, Uzunov P. Eksperimentalni prouchvaniia za khepatoprotektivnata aktivnost na izolirani flavonoidi ot Amorpha fructiosa [Experimental research on the hepatoprotective activity of flavonoids isolated from Amorpha Fructiosa]. Eksp Med Morfol. 1985;24(2):50–4. Bulgarian.

    CAS  PubMed  Google Scholar 

  15. Anna Lis &Józef Góra. Essential oil of Amorpha fruticosa L. J Essent Oil Res. 2001;13(5):340–2.

    Article  Google Scholar 

  16. Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017;7:42717.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Daina A, Michielin O, Zoete V. SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules. Nucleic Acids Res. 2019;47(W1):W357–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Stelzer G, Rosen N, Plaschkes I, Zimmerman S, Twik M, Fishilevich S et al. The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses. Curr Protoc Bioinformatics. 2016;54:1.30.1–1.30.33.

  19. Piñero J, Saüch J, Sanz F, Furlong LI. The DisGeNET cytoscape app: exploring and visualizing disease genomics data. Comput Struct Biotechnol J. 2021;19:2960–7. https://doiorg.publicaciones.saludcastillayleon.es/10.1016/j.csbj.2021.05.015.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Philippe, Bardou. Jérôme Mariette, Frédéric Escudié, Christophe Djemiel, Christophe Klopp. Jvenn: an interactive Venn diagram viewer. BMC Bioinformatics. 2014;15:293.

    Article  Google Scholar 

  21. Szklarczyk D, Morris JH, Cook H, Kuhn M, Wyder S, Simonovic M, et al. The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible. Nucleic Acids Res. 2017;45(D1):D362–8.

    Article  CAS  PubMed  Google Scholar 

  22. Sherman BT, Hao M, Qiu J, Jiao X, Baseler MW, Lane HC, et al. DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Res. 2022;50(W1):W216–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. de Sousa DP, Damasceno ROS, Amorati R, Elshabrawy HA, de Castro RD, Bezerra DP, et al. Essential oils: Chemistry and pharmacological activities. Biomolecules. 2023;13(7):1144. https://doiorg.publicaciones.saludcastillayleon.es/10.3390/biom13071144.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Alonso L, Fernandes KS, Mendanha SA, Gonçalves PJ, Gomes RS, Dorta ML, et al. In vitro antileishmanial and cytotoxic activities of nerolidol are associated with changes in plasma membrane dynamics. Biochim Biophys Acta Biomembr. 2019;1861(6):1049–56.

    Article  CAS  PubMed  Google Scholar 

  25. de Moura DF, Rocha TA, de Melo Barros D, da Silva MM, Dos Santos Santana M, Neta BM, et al. Evaluation of the antioxidant, antibacterial, and antibiofilm activity of the sesquiterpene nerolidol. Arch Microbiol. 2021;203(7):4303–11.

    Article  PubMed  Google Scholar 

  26. Ramazani E, Akaberi M, Emami SA, Tayarani-Najaran Z. Pharmacological and biological effects of alpha-bisabolol: an updated review of the molecular mechanisms. Life Sci. 2022;304:120728.

    Article  CAS  PubMed  Google Scholar 

  27. Nam SY, Kim HY, Kim HM, Jeong HJ. Βeta-eudesmol reduces stem cell factor-induced mast cell migration. Int Immunopharmacol. 2017;48:1–7.

    Article  CAS  PubMed  Google Scholar 

  28. Bomfim DS, Ferraz RP, Carvalho NC, Soares MB, Pinheiro ML, Costa EV, Bezerra DP. Eudesmol isomers induce caspase-mediated apoptosis in human hepatocellular carcinoma HepG2 cells. Basic Clin Pharmacol Toxicol. 2013;113(5):300–6.

    Article  CAS  PubMed  Google Scholar 

  29. Chavan MJ, Wakte PS, Shinde DB. Analgesic and anti-inflammatory activity of Caryophyllene oxide from Annona squamosa L. bark. Phytomedicine. 2010;17(2):149–51.

    Article  CAS  PubMed  Google Scholar 

  30. Delgado C, Mendez-Callejas G, Celis C. Caryophyllene Oxide, the active compound isolated from leaves of Hymenaea courbaril L. (Fabaceae) with Antiproliferative and apoptotic effects on PC-3 androgen-independent prostate Cancer Cell line. Molecules. 2021;26(20):6142.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Chen J, Liang J, Liu S, Song S, Guo W, Shen F. Differential regulation of AKT1 contributes to survival and proliferation in hepatocellular carcinoma cells by mediating Notch1 expression. Oncol Lett. 2018;15(5):6857–64.

    PubMed  PubMed Central  Google Scholar 

  32. Bang J, Jun M, Lee S, Moon H, Ro SW. Targeting EGFR/PI3K/AKT/mTOR signaling in Hepatocellular Carcinoma. Pharmaceutics. 2023;15(8):2130.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Chen Y, Chen HN, Wang K, Zhang L, Huang Z, Liu J, et al. Ketoconazole exacerbates mitophagy to induce apoptosis by downregulating cyclooxygenase-2 in hepatocellular carcinoma. J Hepatol. 2019;70(1):66–77.

    Article  CAS  PubMed  Google Scholar 

  34. Hu X, Pan H, Zhou S, Pang Q, Wang Y, Zhu C, et al. HS1BP3, transcriptionally regulated by ESR1, promotes hepatocellular carcinoma progression. Biochem Biophys Res Commun. 2022;623:111–9.

    Article  CAS  PubMed  Google Scholar 

  35. Li Y, Zhou Y, Ma L, Liu D, Dai Z, Shen J. Mir-3677-3p promotes hepatocellular carcinoma progression via inhibiting GSK3β. Acta Biochim Biophys Sin (Shanghai). 2020;52(12):1404–12.

    Article  CAS  PubMed  Google Scholar 

  36. Zhao Y, Tan H, Zhang X, Zhu J. Roles of peroxisome proliferator-activated receptors in hepatocellular carcinoma. J Cell Mol Med. 2024;28(5):e18042.

  37. Zhang MS, Cui JD, Lee D, Yuen VW, Chiu DK, Goh CC, et al. Hypoxia-induced macropinocytosis represents a metabolic route for liver cancer. Nat Commun. 2022;13(1):954.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Sun H, Qian X, Yang W, Zhou W, Zhou C, Liu S, et al. Novel prognostic signature based on HRAS, MAPK3 and TFRC identified to be associated with ferroptosis and the immune microenvironment in hepatocellular carcinoma. Am J Transl Res. 2022;14(10):6924–40.

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Yu C, Zhang X, Wang M, Xu G, Zhao S, Feng Y, et al. Afatinib combined with anti-PD1 enhances immunotherapy of hepatocellular carcinoma via ERBB2/STAT3/PD-L1 signaling. Front Oncol. 2023;13:1198118. https://doiorg.publicaciones.saludcastillayleon.es/10.3389/fonc.2023.1198118.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Shrestha R, Bridle KR, Crawford DHG, Jayachandran A. TNF–α–mediated epithelial–to–mesenchymal transition regulates expression of immune checkpoint molecules in hepatocellular carcinoma. Mol Med Rep. 2020;21(4):1849–60.

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Liu G, Yin L, Ouyang X, Zeng K, Xiao Y, Li Y. M2 macrophages promote HCC Cells Invasion and Migration via miR-149-5p/MMP9 signaling. J Cancer. 2020;11(5):1277–87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Singh V, Ram M, Kumar R, Prasad R, Roy BK, Singh KK. Phosphorylation: implications in Cancer. Protein J. 2017;36(1):1–6.

    Article  CAS  PubMed  Google Scholar 

  43. Lin Y, Jiang M, Chen W, Zhao T, Wei Y. Cancer and ER stress: mutual crosstalk between autophagy, oxidative stress and inflammatory response. Biomed Pharmacother. 2019;118:109249.

    Article  CAS  PubMed  Google Scholar 

  44. Elzamzamy OM, Penner R, Hazlehurst LA. The role of TRPC1 in modulating Cancer Progression. Cells. 2020;9(2):388.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Wang Y, Qi YX, Qi Z, Tsang SY. TRPC3 regulates the proliferation and apoptosis resistance of Triple negative breast Cancer cells through the TRPC3/RASA4/MAPK pathway. Cancers (Basel). 2019;11(4):558.

    Article  CAS  PubMed  Google Scholar 

  46. Chay DB, Han GH, Cho H, Kim S, Kim JH. High expression of TRPV-1 is associated with poor prognosis in cervical cancer. Gynecol Oncol. 2019;154:270.

    Article  Google Scholar 

  47. Parenti A, De Logu F, Geppetti P, Benemei S. What is the evidence for the role of TRP channels in inflammatory and immune cells? Br J Pharmacol. 2016;173(6):953–69.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Wang H, Chu F, Zhang XF, Zhang P, Li LX, Zhuang YL, et al. TPX2 enhances the transcription factor activation of PXR and enhances the resistance of hepatocellular carcinoma cells to antitumor drugs. Cell Death Dis. 2023;14(1):64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Wang Y, Su K, Wang C, Deng T, Liu X, Sun S, et al. Chemotherapy-induced acetylation of ACLY by NAT10 promotes its nuclear accumulation and acetyl-CoA production to drive chemoresistance in hepatocellular carcinoma. Cell Death Dis. 2024;15(7):545.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Özkan A, Stolley DL, Cressman ENK, McMillin M, DeMorrow S, Yankeelov TE, et al. Tumor Microenvironment alters Chemoresistance of Hepatocellular Carcinoma through CYP3A4 metabolic activity. Front Oncol. 2021;11:662135.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Wu L, Li J, Liu T, Li S, Feng J, Yu Q, et al. Quercetin shows anti-tumor effect in hepatocellular carcinoma LM3 cells by abrogating JAK2/STAT3 signaling pathway. Cancer Med. 2019;8(10):4806–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Kondo Y, Shen L, Suzuki S, Kurokawa T, Masuko K, Tanaka Y, et al. Alterations of DNA methylation and histone modifications contribute to gene silencing in hepatocellular carcinomas. Hepatol Res. 2007;37(11):974–83.

    Article  CAS  PubMed  Google Scholar 

Download references

Funding

This work was supported by the Key Scientific and Technological Project of Henan Province under Grant (No. 242102310387); Project of Basic Research Fund of Henan Institute of Medical and Pharmacological Sciences under Grant (No. 2024BP0102/2024BP0206/2024BP0203).

Author information

Authors and Affiliations

  1. Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, China

    Yixian Liu, Xiaojun Zhang, Jiacong Hao, Ying Zhao, Min Zou, Huiping Chen & Jintao Zhang

Authors
  1. Yixian Liu
    View author publications

    You can also search for this author inPubMed Google Scholar

  2. Xiaojun Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

  3. Jiacong Hao
    View author publications

    You can also search for this author inPubMed Google Scholar

  4. Ying Zhao
    View author publications

    You can also search for this author inPubMed Google Scholar

  5. Min Zou
    View author publications

    You can also search for this author inPubMed Google Scholar

  6. Huiping Chen
    View author publications

    You can also search for this author inPubMed Google Scholar

  7. Jintao Zhang
    View author publications

    You can also search for this author inPubMed Google Scholar

Contributions

Yixian Liu, Huiping Chen and Jintao Zhang contributed to the study conception and design. Material preparation, data collection and analysis were performed by Xiaojun Zhang, Jiacong Hao and Ying Zhao, Huiping Chen and Min Zou reviewed and checked all the experimental data. The first draft of the manuscript was written by Yixian Liu, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Huiping Chen or Jintao Zhang.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, Y., Zhang, X., Hao, J. et al. Essential oils from Amorpha fruticosa against hepatocellular carcinoma based on network pharmacology. BMC Complement Med Ther 25, 29 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12906-025-04766-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12906-025-04766-5

Keywords

BMC Complementary Medicine and Therapies

ISSN: 2662-7671

Contact us