Natural Bioactive Compounds Promote Cell Apoptosis in Gastric Cancer Treatment: Evidence from Network Pharmacological Study and Experimental Analysis

Wang, Yan; Wang, Haiyang; Xu, Shun

doi:https://doi.org/10.1155/2023/6316589

Journal of Chemistry

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Abstract Introduction Methods Results Discussion Data Availability Disclosure Conflicts of Interest Acknowledgments Supplementary Materials References Copyright Related Articles

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Natural Bioactive Compounds: Chemistry, Extraction, and Applications

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Research Article | Open Access

Volume 2023 | Article ID 6316589 | https://doi.org/10.1155/2023/6316589

Natural Bioactive Compounds Promote Cell Apoptosis in Gastric Cancer Treatment: Evidence from Network Pharmacological Study and Experimental Analysis

Yan Wang,¹Haiyang Wang,¹and Shun Xu¹

Academic Editor: Marwa Fayed

Received04 Sept 2022

Revised09 Nov 2022

Accepted25 Nov 2022

Published06 Feb 2023

Abstract

Background. Gastric cancer (GC) is one of the most lethal cancers. Shenlian capsule (SLC) is a Chinese patent medicine made from 11 herbs containing numerous plant-derived compounds, and the clinical trials of SLCs confirmed that they had effective adjuvant therapy for a variety of cancer such as lung cancer and gastric cancer. Moreover, the HPLC fingerprint of SLCs was established from other research to find potential components. In this study, network pharmacology-based research was used to identify combinations with molecules, targets, and pathways to explore their interaction mechanisms. Methods. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and the Traditional Chinese Medicine Integrated Database (TCMID) were widely implemented in selecting the active chemical components of SLCs with an oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 18%. In addition, the TCMSP and TCMID databases obtained the targets of SLCs, and PharmMapper (PM) was used to predict targets of SLCs. Gastric cancer-related genes were provided by the GeneCards and TTD databases. Subsequently, the drug/target/pathway network was established and visualized using Cytoscape software. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) enrichment analyses were used to predict the potential genes and pathways of gastric cancer. Molecular docking was performed to study the interaction between ligands and targets; the interaction was visualized using Discovery Studio and PyMOL. Finally, the potential primary mechanism used by SLCs against gastric cancer was verified by cell experiments, including MTT cell apoptosis assay, flow cytometry cell cycle assay, and western blotting with HGC-27 cells (undifferentiated). Results. Of 213 active chemical components from SLCs, 35 primary active chemical components were identified, and 10 potential critical targets were selected from the 185 intersections of the targets of SLCs and GC, such as RAC-alpha serine/threonine kinase 1 (AKT1), cellular tumor antigen p53 (TP53), interleukin-6 (IL6), caspase-3 (CASP3), vascular endothelial growth factor A (VEGFA), and epidermal growth factor receptor (EGFR). GO and KEGG enrichment analysis provided the PI3K/AKT, TNF, and p53 signaling pathways, which may be the primary signaling pathways modulating gastric cancer. Molecular docking verified targets such as AKT1, TP53, EGFR, and CASP3, which exhibited satisfactory binding capacity with active ingredients. Experiments with HCG-27 cells confirmed that SLCs may provide favorable treatment for GC by promoting CASP3 and TP53 expression to induce cell apoptosis and provided the predictions for network pharmacology and molecular docking. MTT and flow cytometry assays verified that SLCs promoted cell apoptosis and inhibited cell proliferation by triggering G0/G1 and S cell cycle arrest. In addition, western blot analysis confirmed that SLCs promoted TP53 and CASP3 overexpression, which led to HGC-27 gastric cell apoptosis. Conclusions. Our results confirmed that SLCs inhibit proliferation of HGC-27 gastric cell by promoting cell apoptosis and, therefore, have potential in the treatment of advanced gastric cancer. P53 signaling pathway was the key pathway. In addition, quercetin, matrine, and ursolic acid might be the main active ingredients.

1. Introduction

Gastric cancer (GC), a common malignant tumor, has become the fourth most lethal cancer worldwide, as reported in the 2020 GLOBOCAN project by the International Agency for Research on Cancer (IARC) [1]. Gastric cancer is classically divided into intestinal and diffuse histologic types, and most cases of gastric cancer were induced by infection with the bacterium Helicobacter pylori [2]. Currently, patients with advanced gastric cancer usually choose chemotherapy and radiotherapy as the major treatment due to a lack of effective surgical treatments and a late diagnosis. Despite this, the survival rate for patients with advanced gastric cancer remains dismal [3, 4]. Doxorubicin hydrochloride (Dox), irinotecan (CPT-11), and esophagogastroduodenoscopy (EGD) are commonly used to treat gastric cancer. However, drug resistance is frequently observed in the treatment of GC, and therefore, it is necessary to find new and effective drugs for treatment. Natural bioactive compounds have potential as a cancer therapy; therefore, the uses of natural bioactive compounds have become one of the hottest topics worldwide.

Traditional Chinese medicine (TCM) has been widely used in the treatment of cancer because natural bioactive compounds have the capability of exerting synergistic effects upon multiple targets [5–7]. To exemplify, Xiao-Ai-Ping (XAP) injection has been effectively used to treat gastric cancer and lung cancer [8, 9], and Weikang Keli has also been used for gastric cancer therapy in cell experiments [10]. Thus, there is promising potential for TCM to be used to treat advanced gastric cancer.

Shenlian capsule (SLC) is a Chinese patent medicine that is prepared from 11 Chinese herbs: Danshen (Radix Salviae Miltiorrhizae/Chinese salvia (Salvia miltiorrhiza Bunge)), Kushen (Radix Sophorae Flavescentis Radix/shrubby sophora (Sophora flavescens Aiton)), Banzhilian (Herba Scutellariae Barbatae/barbed skullcap (Scutellaria barbata D. Don.)), Shandougen (Radix et Rhizome Sophorae Tonkinensis/bushy sophora (Sophora tonkinensis Gagnep.)), Baibiandou (Semen Lablab Album/hyacinth bean (Dolichos lablab L.)), Sanleng (Rhizoma Sparganii/common bur-reed (Sparganium stoloniferum Buch.-Ham.)), Ezhu (Rhizoma Curcumae (Zedoariae)/zedoary root (Cucurma zedoaria (Christm.) Roscoe), Fangji (Radix Stephaniae Tetrandrae/stephania root (Stephania tetrandra S. Moore)), Wumei (Fructus Mume/dried black plum (Prunus mume (Sieb. et Zucc.))), Buguzhi (Fructus Psoraliae/babchi (Psoralea corylifolia L.)), and Kuxingren (Semen Armeniacae Amarum/apricot seeds (Prunus armeniaca L.)). SLCs have already been used for the treatment of lung cancer and gastric cancer. The high performance liquid chromatography (HPLC) fingerprint of Shenlian also established by Han’ s team to find the potential ingredients of SLCs. Nine components were identified such as oxymatrine, matrine, tetrandrine, fangchinoline, amygdalin, oleanolic acid, ursolic acid, psoralen, and angelicin [11–13]. Several clinical trials in China have confirmed that adjuvant treatment with SLCs was effective with bevacizumab injection, epirubicin hydrochloride injection, cisplatin injection, or fluorouracil injection for advanced gastric cancer [14, 15]. However, the treatment and action mechanisms of the SLC remain undefined. Thus, a network pharmacology-based study, which was proposed by Hopkins and relies on network database retrieval, system biology, and pharmacology, should be undertaken to elucidate SLCs’ potential treatment mechanism in gastric cancer [16–18]. Network pharmacology-based studies have the ability to determine the primary potential ingredients, targets, and pathways involved [19, 20].

To further identify the mechanism of action of the SLCs, molecular docking was used to validate combination ingredients with targets [21]. The binding energy and bond interacitons between ingredients and targets interpreted the biological activity of the SLCs’ main ingredients.. By also conducting MTT cell apoptosis assay, flow cytometry, and western blot analysis, the specific mechanisms used by the SLC to regulate gastric cancer cell apoptosis, cell cycle arrest, and their signal transduction pathways were elucidated [22]. Finally, the mechanisms used by the SLC against GC were clarified through the above research, and a schematic flow diagram is shown in Figure 1.

2. Methods

2.1. Main Active Ingredients and Target Identification

The main active chemical ingredients in all the herbs in the SLC were found in the Traditional Chinese Medicine Systems Pharmacology (TCMSP; https://tcmsp-e.com/tcmsp.php) database and Traditional Chinese Medicine Integrated Database (TCMID; https://www.megabionet.org/tcmid/). These components were identified based on oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 18%. The targets of the main components were obtained from TCMSP and TCMID, and the predictions of the SLC’s potential targets were obtained from the PharmMapper database (PM; https://www.lilab-ecust.cn/pharmmapper/) based on a z score ≥4. The UniProt database (https://www.uniprot.org/) and DrugBank database (https://www.drugbank.ca) provided the human genes related to these targets. GC targets were selected from the GeneCards database (https://www.genecards.org/) and TTD database (https://bidd.nus.edu.sg/group/ttd/ttd.asp) by searching using the keywords “gastric cancer,” “stomach cancer,” and “gastric carcinoma.”

2.2. Drugs/Targets/Pathways and Protein-Protein Interaction Network Construction

The targets and potential active ingredients were imported into Cytoscape (v. 3.8.0) for the construction of a drug/target/pathway network. By selecting high-degree targets and active ingredients, key targets and main active ingredients were mined. Protein-protein interaction (PPI) networks were constructed using STRING tools (https://string-db.org) and Cytoscape to find the potential leader targets.

2.3. GO and KEGG Enrichment Analysis

Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) enrichment analyses were applied from the DAVID database (https://david.ncifcrf.gov/) based on a value < 0.05 as the condition to visualize the results and confirm key signaling pathways.

2.4. Molecular Docking Analyses

The 3D structures of proteins were downloaded from the Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank database (https://www.rcsb.org/). The chosen scientific name of the source organism was Homo sapiens, and it was refined at resolutions of 1.0–3.0 A°. Ligands were downloaded from TCMSP and TCMID and generated using ChemDraw (v. 14.0). AutoDockTools (v. 1.5.6) was used to prepare the input files, and AutoDock Vina was used to calculate the affinities between these proteins and ligands. Then, the docking results, which are docking binding energies based on the threshold conditions of ≤ −8.0 kcal/mol, were collected and were then integrated and visualized using PyMOL (v. 2.3.0) and Discover Studio (v. 2017).

2.5. Experimental Analysis

2.5.1. Cell Culture

HGC-27 (undifferentiated) gastric cells were provided by Procell Life Science & Technology (Wuhan, China). The cells were grown in Roswell Park Memorial Institute (RPMI)-1640 medium with fetal bovine serum (20%, FBS) (HyClone, China) and a mixture of 1% antibiotics (streptomycin 100 U/mL and penicillin 100 U/mL) in an incubator containing 5% CO₂ at 37°C. The culture medium was replaced every 2-3 days at both the apical and basolateral ends. After 90% confluence, the cells were subcultured on plates.

2.5.2. MTT Analysis

HGC-27 cells were digested with trypsin to produce a single-cell suspension, followed by their seeding in a 96-well plate at 3 × 10⁴ cells/well. After incubation for 24 h, the cells were incubated with different concentrations of SLC solution (0 g/L, 0.25 g/L, 0.5 g/L, 1 g/L, 2 g/L, and 4 g/L) in a constant temperature incubator at 37°C for 48 h. After the end of the culture, 100 μL MTT was added to each well. After 4 h, the MTT solution was removed, and 150 μL DMSO was added. The plate was then shaken for 10 min at a low speed, and the OD value was determined at 490 nm by an enzyme labeling instrument.

2.5.3. Investigation of Apoptosis and Cell Cycle through Flow Cytometry

The HGC-27 cells were divided into three groups: blank, control (SLC 0 g/L), and experimental (SLC 2 g/L and 4 g/L). Then, the HGC-27 cells were inoculated into a 6-well plate. After 48 h of corresponding treatment in an incubator containing 5% CO₂ at 37°C, cells from each group were collected and washed using phosphate-buffered saline (PBS), 0.5 mL trypsin was added, and the cells were then centrifuged. Flow cytometry was subsequently performed to analyze the cell cycle.

2.5.4. Western Blotting

The samples were lysed on ice for 20 min and centrifuged for 20 min (12,000 rpm, 4°C), and the supernatant was then removed. Then, the concentrations of proteins were measured using a BCA Protein Assay Kit (Solarbio, Beijing, China). After adjusting the protein concentration using 5× loading buffer and PBS, the samples were boiled at 95°C for 5 min and prepared for electrophoresis. After electrophoresis, electroblotting was performed to transfer the proteins to a polyvinylidene fluoride (PVDF) membrane. Five percent nonfat milk was used to block the PVDF membranes for 2 h, and then western blotting was performed with the primary antibodies against CASP3, Akt, phosphorylated Akt, and p53 at 4°C for 12 h. All of the primary antibodies were diluted in a ratio of 1 : 1000. After that, Tris-buffered saline (TBS) containing 0.1% Tween-20 (TBST) was used to wash the PVDF membranes 3 times, for 10 min each time. Horseradish peroxidase (HRP)-conjugated secondary antibodies were diluted in a ratio of 1 : 1500 and incubated with the PVDF membranes for 1 h at room temperature. The PVDF membranes were then washed with TBST 3 times and 10 min each time. The enhancement solution in the ECL reagent was mixed with the stable peroxidase solution in a 1 : 1 ratio, and the immunoreactive protein bands were imaged by a fully automated chemiluminescence image analysis system. Then, TBST was used to wash the PVDF membranes 3 times, for 5 min each time, and the PVDF membranes were then recovered and regenerated. The PVDF membranes were blocked again and incubated with secondary antibodies, with the other parameters remaining unchanged. ImageJ software (National Institutes of Health, Bethesda, MD, USA) was used for the gray value analysis.

3. Results

3.1. Main Active Ingredients and Target Identification

A total of 386 potential targets were identified from the TTD database and GeneCards database. After comparison with the targets of the SLC, 185 potential targets associated with GC and the SLC were obtained from the database screening and prediction, as shown in Figure 2.

There were 855 active components retrieved from the TCMSP database and the TCMID in which OB ≥ 30% and DL ≥ 18%. Some of the basic information about these active components is shown in Table 1.

3.2. Drug/Target/Pathway and Protein-Protein Interaction Network Construction

The active components and targets were input into Cytoscape to construct the network of “drugs/targets/pathways,” as shown in Figure 3. Thirty-five main potential active ingredients were mined from the network, as shown in Table 2. It has already been shown that common ingredients such as quercetin, ursolic acid, and kaempferol possess anticancer activity. Thus, they might be the main potential ingredients. In addition, wogonin and moslosooflavone may also play a very important role in the treatment of GC.

The protein-protein interaction network diagrams were obtained from STRING tools and Cytoscape, as shown in Figure 4. The protein-protein interaction network diagrams indicated that AKT1, TP53, VEGFA, and CASP3 might be key targets.

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(b)

3.3. GO and KEGG Enrichment Analysis

The main potential genes and pathways were determined using GO and KEGG enrichment analysis, as shown in Figures 5 and 6. The primary signaling pathways may be those of PI3K-Akt, TNF, FoxO, and p53. The pathways in cancer were the most significantly enriched. The PI3K-Akt signaling pathway regulates cell survival and cell cycle, the TNF signaling pathway, and the FoxO signaling pathway. The p53 signaling pathway regulates cell apoptosis. These pathways had well correlation with AKT1, TP53, CASP3, and EGFR that were the main potential genes of SLC because these pathways are highly involved in cancer development. The main potential ingredients of SLC like quercetin, matrine, ursolic acid, and stigmasterol can exert antitumor effects by altering cell cycle progression, inhibiting cell proliferation, promoting apoptosis, inhibiting angiogenesis and metastasis progression, and affecting autophagy found from previous studies. Hence, the main potential ingredients of SLC could regulate the expression of BP, CC, and MF to regulate cell apoptosis and cell cycle. The SLC regulated well with the expression of these pathways when administered for treatment for advanced gastric cancer.

3.4. Molecular Docking Analyses

Ten proteins and 35 ingredients were selected for the molecular docking analysis. Several results of molecular docking are shown in Table 3. The key targets such as AKT1, TP53, and CASP3 were able to strongly bind with quercetin, wogonin, and (2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one, as shown in Figure 7. To exemplify, the binding energy between wogonin and TP53 was approximately −7.9 kcal/mol. Val147 and Pro223 were involved in pi-sigma bonding, and Cys220 formed pi-sulfur interactions with the cyclic ring. Pro153 and Pro222 formed pi-alkyl interactions with the cyclic ring, which shows the potential hydrophobic interactions. Glu221 formed amide-pi stacked interactions with the cyclic ring. The molecular docking results indicated that there was stronger binding activity of the SLC’s active ingredients with the primary targets of GC, which may imply that the SLC regulates the expression of the main pathways by combining with key targets. Besides, the results of binging energy between main ingredients such as stigmasterol, matrine, and main targets such as AKT1, TP53, CASP3, and EGFR also suggested that the main ingredients can control cell apoptosis and cell cycle to reduce the content of cancer cells The molecular docking results are shown in Table 3.

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3.5. Experimental Analysis

3.5.1. MTT Analysis

The SLC’s antitumor effect on GC was confirmed by MTT assay, as shown in Figure 8. The results show that there was excellent effectiveness by the mid and high concentrations of the SLC in killing HGC-27 undifferentiated gastric cancer cells. The highest inhibition rate was up to 79.57% with different concentrations of the SLC solution (4 g/L) in a constant temperature incubator at 37°C for 48 h. Low cell viability was aided by the variety of ingredients, and the problem of drug resistance was solved. Therefore, the results of MTT analysis corroborate well with the conclusions of molecular docking. The ingredients of SLC such as quercetin, ursolic acid, stigmasterol, and matrine combined with key targets to prohibit cell apoptosis.

3.5.2. Investigation of Apoptosis and Cell Cycle through Flow Cytometry

To investigate the effect of the SLC combination on the cell cycle distribution, flow cytometry was used, as shown in Figure 9. The results collectively show that the SLC exerts a mild effect on the cell cycle in HGC-27 cells. Cells were blocked in S phase at medium SLC concentrations and blocked in G1 phase at high SLC concentrations. The results of the flow cytometry assay proved that the main mechanism of action was regulation of apoptosis instead of decreasing cell proliferation. The results of flow cytometry evidenced the predictions of network pharmacology and molecular docking. SLC regulated cell cycle to promote apoptosis of HGC-27 cells.

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3.5.3. Western Blotting

To confirm the results of network pharmacology, western blotting was used, as shown in Figure 10. We inferred that the SLC enhances proapoptotic gene expression, such as that of caspase-3 and TP53, to promote apoptosis. This result confirmed the potential targets studied from network pharmacology and molecular docking. We also verified the results of network pharmacology research. However, the inhibition of Akt and phosphorylated Akt was insufficient. We speculated that the reason for this may be a lack of effect on the cell cycle by the SLC. Quercetin, ursolic acid, stigmasterol, and matrine played very important role in the treatment. The results of western blotting justified that these main ingredients of SLC promote cell apoptosis to treat GC.

4. Discussion

Natural bioactive compounds are widely used to treat various diseases, especially cancers [23]. Natural products with potential for gastric cancer treatment have received much attention [24]. The possible mechanisms responsible for the effect of the SLCs in the treatment of advanced gastric cancer were proposed in this study. The main natural bioactive compounds of SLCs were identified by HPLC, and network pharmacology was used to identify the main potential active ingredients and targets [25]. SLCs may fortify the p53 signaling pathway and inhibit the PI3K/AKT signaling pathway to promote gastric cancer cell apoptosis. The p53 and PI3K/AKT signaling pathways play an important role in the apoptotic signaling circuitry [25, 26]. GO and KEGG enrichment analysis revealed that TP53, caspase-3, and AKT1 might be the key targets [27]. Network pharmacology study pointed out the relationship between ingredients of SLC such as quercetin, matrine, ursolic acid, and stigmasterol and key targets such as AKT1, EGFR, CASP3, and TP53, as shown in Figures 5 and 6. The main ingredients of SLC might promote cell apoptosis and regulate cell cycle for GC therapy, and quercetin, matrine, and stigmasterol might be the main active natural bioactive compounds. In addition, numerous studies have already identified that these ingredients are potential anticancer agents and natural bioactive compounds can be expected to address clinical drug resistance [28–30], and the accuracy of the prediction was confirmed.

Furthermore, molecular docking revealed the results of ingredients binding to targets. There were excellent docking results for quercetin, beta-sitosterol, ursolic acid, matrine, and stigmasterol. These main ingredients were docked with main targets such as AKT1, CASP3, TP53, and EGFR. The results of molecular docking confirmed that SLC’s ingredients could combine with these key targets to control PI3K-Akt signaling pathway, p53 signaling pathway, and TNF signaling pathway. This matched the network pharmacology study’s interpretation and offered a cell experimental basis for the use of key targets as therapeutic targets. This adds further evidence that the natural bioactive compounds in SLC have promising effect on GC.

Moreover, the results of cell experimental were in a good agreement with the network pharmacology and molecular docking results. The MTT assay and flow cytometry also confirmed that SLCs can prompt the apoptosis and inhibit proliferation of HGC-27 cells. Although the SLC exerted a mild effect on the cell cycle in HGC-27 cells, cell viability decreased to 11.43% after HGC-27 cells were incubated with high concentrations of the SLC. This matches the results of previous studies and pointed out that the ingredients of SLC could promote cell apoptosis and control cell cycle to reduce the viability of HGC-27 cells in vitro. Western blotting confirmed that the SLC upregulated the protein expression of TP53 and caspase-3 protein, which consequently promoted cell apoptosis [31–34]. This confirmed that the ingredients of SLC regulated the expression of the TNF signaling pathway and p53 signaling pathway and led to cell apoptosis. The accuracy of network pharmacology and molecular docking prediction results must be verified by experimental assay.

Nevertheless, we systematically demonstrated the potential mechanism of the SLCs and confirmed that the SLC’s action in the treatment of advanced gastric cancer is the regulation of the p53 signaling pathway overexpression. The main active natural bioactive compounds might be quercetin, matrine, ursolic acid, and stigmasterol. As a TCM that is rich in plant-derived compounds, there is great potential for the SLC to play a more significant role in the treatment of advanced gastric cancer. Moreover, the natural bioactive compounds such as quercetin, matrine, and ursolic acid are useful in the therapy of gastric cancer. Natural products are considered a source for bioactive compounds and have potential for developing some novel therapeutic agents.

Data Availability

All the data and materials used in the current study are available from the corresponding author upon reasonable request.

Disclosure

The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Conflicts of Interest

The authors declare that they have no conflicts of interest.

Acknowledgments

This study was supported by the Postgraduate Education Reform and Quality Improvement Project of Henan Province (YJS2021AL014 and YJS2022ZX06). This study was also supported by the National Supercomputing Center in Zhengzhou. The authors thank LetPub (https://www.letpub.com/) for its linguistic assistance during the preparation of this manuscript.

Supplementary Materials

Supplementary Figure 1: the drug/target/pathway network. Supplementary Figure 2: the raw data of MTT assay. Supplementary PDF1: the raw data of flow cytometry W1. Supplementary PDF2: the raw data of flow cytometry W2. Supplementary PDF3: the raw data of flow cytometry W3. Supplementary PDF4: the raw data of western blot. (Supplementary Materials)

References

H. Sung, J. Ferlay, R. L. Siegel et al., “Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries,” CA: A Cancer Journal for Clinicians, vol. 71, no. 3, pp. 209–249, 2021.
View at: Publisher Site | Google Scholar
A. H. Chang and J. Parsonnet, “Role of bacteria in oncogenesis,” Clinical Microbiology Reviews, vol. 23, no. 4, pp. 837–857, 2010.
View at: Publisher Site | Google Scholar
R. E. Sexton, M. N. Al Hallak, M. Diab, and A. S. Azmi, “Gastric cancer: a comprehensive review of current and future treatment strategies,” Cancer & Metastasis Reviews, vol. 39, no. 4, pp. 1179–1203, 2020.
View at: Publisher Site | Google Scholar
Z. Song, Y. Wu, J. Yang, D. Yang, and X. Fang, “Progress in the treatment of advanced gastric cancer,” Tumor Biology, vol. 39, no. 7, Article ID 101042831771462, 2017.
View at: Publisher Site | Google Scholar
K. Wang, Q. Chen, Y. Shao et al., “Anticancer activities of TCM and their active components against tumor metastasis,” Biomedicine & Pharmacotherapy, vol. 133, Article ID 111044, 2021.
View at: Publisher Site | Google Scholar
Y. Liu, S. Yang, K. Wang et al., “Cellular senescence and cancer: focusing on traditional Chinese medicine and natural products,” Cell Proliferation, vol. 53, no. 10, Article ID e12894, 2020.
View at: Publisher Site | Google Scholar
Y. Xiang, Z. Guo, P. Zhu, J. Chen, and Y. Huang, “Traditional Chinese medicine as a cancer treatment: modern perspectives of ancient but advanced science,” Cancer Medicine, vol. 8, no. 5, pp. 1958–1975, 2019.
View at: Publisher Site | Google Scholar
X. L. Hu and X. S. Liu, “Clinical effect of Xiaoaiping injection combined with gemcitabine and carboplatin in treatment of IIIB and IV non-small cell lung cancer,” Drug Evaluation Research, vol. 40, pp. 266–269, 2017, in China.
View at: Google Scholar
J. R. Liu, Y. H. An, W. B. Yang, and K. Zhao, “Clinical study on Xiaoaiping injection combined with GP regimen in the treatment of advanced lung squamous cell carcinoma,” Medical Innovation of China, vol. 13, pp. 97–101, 2016, in China.
View at: Google Scholar
J. Huo, F. Qin, X. Cai et al., “Chinese medicine formula ‘Weikang Keli’ induces autophagic cell death on human gastric cancer cell line SGC-7901,” Phytomedicine, vol. 20, no. 2, pp. 159–165, 2013.
View at: Publisher Site | Google Scholar
Y. C. Hung, T. L. Pan, and W. L. Hu, “Roles of reactive oxygen species in anticancer therapy with salvia miltiorrhiza Bunge,” Oxidative Medicine and Cellular Longevity, vol. 2016, Article ID 5293284, 10 pages, 2016.
View at: Publisher Site | Google Scholar
X. Cao and Q. He, “Anti-tumor activities of bioactive phytochemicals in Sophora flavescens for breast cancer,” Cancer Management and Research, vol. 12, pp. 1457–1467, 2020.
View at: Publisher Site | Google Scholar
Q. Han, Z. Bin, L ping, and G. Zhi-hu, “Quality evaluation of Shenlian capsules by HPLC fingerprint and pattern recognition,” Chinese Journal of Pharmaceutical Analysis, vol. 40, no. 07, pp. 1300–1308, 2020, in China.
View at: Google Scholar
Z. Diao, “The clinical effects of Shenlian capsule, trastuzumab combined with SOX regimen in the treatment for HER-2 positive advanced gastric carcinoma,” International Journal of Translation & Community Medicine, vol. 40, no. 117, pp. 1020–1024, 2018, in China.
View at: Google Scholar
T. XiaoHui, “Clinical study on Shenlian capsule combined with DP therapeutic regimen in treatment of advanced gastric cancer,” Drugs and Clinic, vol. 33, no. 8, pp. 2055–2059, 2018, in China.
View at: Google Scholar
A. L. Hopkins, “Network pharmacology: the next paradigm in drug discovery,” Nature Chemical Biology, vol. 4, no. 11, pp. 682–690, 2008.
View at: Publisher Site | Google Scholar
B. Boezio, K. Audouze, P. Ducrot, and O. Taboureau, “Network-based approaches in pharmacology,” Molecular Informatics, vol. 36, no. 10, Article ID 1700048, 2017.
View at: Publisher Site | Google Scholar
C. Nogales, Z. M. Mamdouh, M. List, C. Kiel, A. I. Casas, and H. H. Schmidt, “Network pharmacology: curing causal mechanisms instead of treating symptoms,” Trends in Pharmacological Sciences, vol. 43, no. 2, pp. 136–150, 2022.
View at: Publisher Site | Google Scholar
X. Wang, Z. Y. Wang, J. H. Zheng, and S. Li, “TCM network pharmacology: a new trend towards combining computational, experimental and clinical approaches,” Chinese Journal of Natural Medicines, vol. 19, no. 1, pp. 1–11, 2021.
View at: Publisher Site | Google Scholar
R. Zhang, X. Zhu, H. Bai, and K. Ning, “Network pharmacology databases for traditional Chinese medicine: review and assessment,” Frontiers in Pharmacology, vol. 10, p. 123, 2019.
View at: Publisher Site | Google Scholar
L. Pinzi and G. Rastelli, “Molecular docking: shifting paradigms in drug discovery,” International Journal of Molecular Sciences, vol. 20, no. 18, p. 4331, 2019.
View at: Publisher Site | Google Scholar
T. Hussain, S. Bajpai, M. Saeed et al., “Potentiating effect of ethnomedicinal plants against proliferation on different cancer cell lines,” Current Drug Metabolism, vol. 19, no. 7, pp. 584–595, 2018.
View at: Publisher Site | Google Scholar
S. Wang, S. Long, Z. Deng, and W. Wu, “Positive role of Chinese herbal medicine in cancer immune regulation,” The American Journal of Chinese Medicine, vol. 48, no. 7, pp. 1577–1592, 2020.
View at: Publisher Site | Google Scholar
J. Xu, F. Kang, W. Wang, S. Liu, J. Xie, and X. Yang, “Comparison between heat-clearing medicine and antirheumatic medicine in treatment of gastric cancer based on network pharmacology, molecular docking, and tumor immune infiltration analysis,” Evidence-based Complementary and Alternative Medicine, vol. 2022,, 21 pages, 2022.
View at: Publisher Site | Google Scholar
M. J. Duffy, N. C. Synnott, and J. Crown, “Mutant p53 as a target for cancer treatment,” European Journal of Cancer, vol. 83, pp. 258–265, 2017.
View at: Publisher Site | Google Scholar
M. Osaki, M. Oshimura, and H. Ito, “PI3K-Akt pathway: its functions and alterations in human cancer,” Apoptosis, vol. 9, no. 6, pp. 667–676, 2004.
View at: Publisher Site | Google Scholar
J. Kania, S. J. Konturek, K. Marlicz, E. G. Hahn, and P. Konturek, “Expression of survivin and caspase-3 in gastric cancer,” Digestive Diseases and Sciences, vol. 48, no. 2, pp. 266–271, 2003.
View at: Publisher Site | Google Scholar
M. Reyes-Farias and C. Carrasco-Pozo, “The anti-cancer effect of quercetin: molecular implications in cancer metabolism,” International Journal of Molecular Sciences, vol. 20, no. 13, p. 3177, 2019.
View at: Publisher Site | Google Scholar
A. J. Vargas, S. Sittadjody, T. Thangasamy, E. E. Mendoza, K. H. Limesand, and R. Burd, “Exploiting tyrosinase expression and activity in melanocytic tumors: quercetin and the central role of p53,” Integrative Cancer Therapies, vol. 10, no. 4, pp. 328–340, 2011.
View at: Publisher Site | Google Scholar
M. S. Bin Sayeed and S. S. Ameen, “Beta-sitosterol: a promising but orphan nutraceutical to fight against cancer,” Nutrition and Cancer, vol. 67, no. 8, pp. 1216–1222, 2015.
View at: Publisher Site | Google Scholar
J. Chen, “The cell-cycle arrest and apoptotic functions of p53 in tumor initiation and progression,” Cold Spring Harbor Perspectives Medicine, vol. 6, no. 3, Article ID a026104, 2016.
View at: Publisher Site | Google Scholar
X. Wang, E. R. Simpson, and K. A. Brown, “p53: protection against tumor growth beyond effects on cell cycle and apoptosis,” Cancer Research, vol. 75, no. 23, pp. 5001–5007, 2015.
View at: Publisher Site | Google Scholar
A. G. Porter and R. U. Jänicke, “Emerging roles of caspase-3 in apoptosis,” Cell Death & Differentiation, vol. 6, no. 2, pp. 99–104, 1999.
View at: Publisher Site | Google Scholar
S. Nagata, “Apoptosis and clearance of apoptotic cells,” Annual Review of Immunology, vol. 36, no. 1, pp. 489–517, 2018.
View at: Publisher Site | Google Scholar

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Copyright © 2023 Yan Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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