The Mechanism of Scopolamine’s Effect on Migration Function of Lung Cancer Cells: A Network Pharmacology and Bioinformatics Perspective

Xiao, Yang; Ma, Mengcong; Gu, Qing; Xiao, Yunfeng

doi:https://doi.org/10.1155/2024/5081383

International Journal of Clinical Practice

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Abstract Introduction Methods Results Discussion Conclusion Data Availability Conflicts of Interest References Copyright Related Articles

Research Article | Open Access

Volume 2024 | Article ID 5081383 | https://doi.org/10.1155/2024/5081383

The Mechanism of Scopolamine’s Effect on Migration Function of Lung Cancer Cells: A Network Pharmacology and Bioinformatics Perspective

Yang Xiao,¹Mengcong Ma,¹Qing Gu,^1,2and Yunfeng Xiao^1,2

Academic Editor: Bing Niu

Received16 Feb 2024

Revised06 May 2024

Accepted15 May 2024

Published28 May 2024

Abstract

Background. This study utilized network pharmacology and bioinformatics analysis to identify the hub genes influenced by scopolamine in lung cancer. Methods. The effect of scopolamine on lung cancer was investigated by cell invasion assay and cell scratch assay. The analysis involved protein-protein interaction (PPI) networks topology analysis to identify these genes, and subsequent differential analysis and survival analysis were conducted using gene expression profile interaction analysis (GEPIA). Furthermore, the findings were supported by molecular docking experiments for verification. Results. Results from cell invasion and scratch assays suggest that scopolamine inhibits the migration of lung cancer cells. JAK2, JAK3, CCR5, and ACE were identified as the top four hub genes that have an impact on lung cancer. KEGG enrichment analysis revealed that the scopolamine response in lung cancer is significantly associated with ten pathways, including “neuroactive ligand-receptor interaction in cancer,” “PD-1 checkpoint pathway in cancer,” “chemokine signaling pathway,” “PD-L1 expression,” and others. Additionally, the expression levels of JAK2, JAK3, CCR5, and ACE were found to be correlated with survival in patients with lung cancer. Furthermore, molecular docking experiments demonstrated that scopolamine binds and forms stable complexes with the protein products of all four aforementioned genes. The main targets of scopolamine in the treatment of lung cancer are JAK2, JAK3, CCR5, and ACE. Conclusion. Scopolamine has a significant effect on various cellular functions in lung cancer cells, potentially reducing the likelihood of metastasis. Based on these findings, it is recommended to consider administering scopolamine as part of the preoperative phase for patients with lung cancer.

1. Introduction

Lung cancer is a malignant tumor that originates from abnormal cells in the lung tissue [1]. It is one of the most prevalent cancers worldwide and a leading cause of mortality [2, 3]. Lung cancer is generally classified into two main types: non-small-cell lung cancer (NSCLC) and small cell lung cancer (SCLC). NSCLC constitutes the majority of lung cancer cases and encompasses subtypes such as adenocarcinoma, squamous cell carcinoma, and large cell carcinoma [4]. The objective of surgery is to completely excise the lung tumor along with potential sites of metastasis [5–7].

Due to the rising prevalence of lung cancer, anesthesia is required for up to 80% of cancer patients during diagnosis, treatment, or palliative care [8–10]. A growing number of patients are undergoing surgical resection of primary or metastatic solid tumors, with the majority requiring anesthesia for the initial surgical removal of their cancer [11, 12].

Compared to traditional Western anesthesia, traditional Chinese medicine anesthesia has some unique advantages [13]. Chinese herbal medicine is usually derived from natural plant or animal ingredients, with fewer toxic side effects and better adaptability to individual patient differences [14]. Chinese medicine anesthesia can be more accurately adjusted in terms of formulation and dosage based on the patient’s constitution, condition, and type of surgery, allowing for personalized treatment effects [15, 16]. Scopolamine, derived from a natural alkaloid found in the Solanaceae family (specifically scopolamine from mandrake), is classified as an anticholinergic drug [17]. Its mechanism of action involves reducing respiratory secretions, maintaining open breathing, and preventing vagal excitation, therefore preventing bradycardia or arrest [18, 19].

Several studies have demonstrated the potential of surgical anesthesia in changing tumor cell status and affecting surgical outcomes [12, 20]. For instance, isoflurane, sevoflurane, and desflurane have been found to significantly impact cancer cell biology, leading to enhanced metastatic potential in ovarian cancer [21–23]. This suggests that these general anesthetics may have an unfavorable effect on carcinomas by facilitating their growth and migration [24]. Therefore, it is crucial to utilize the inhibitory effects of specific anesthetics on tumor metastasis during clinical anesthesia, developing individualized and precise anesthetic plans to reduce the incidence of tumor cell metastasis and ultimately improve postoperative patient survival [25–28]. This study also discovered that scopolamine may have an impact on lung cancer cell metastasis, providing a basis for further investigation [29–32].

This study aims to investigate the mechanism of scopolamine’s impact on lung cancer cell function using network pharmacology and bioinformatics analysis. The goal is to establish a safer and more reliable preanesthetic administration standard that can effectively reduce the rate of postoperative metastasis following tumor resection. Ultimately, the study seeks to improve the survival rate of patients.

2. Methods

2.1. Cell Culture

The A549 lung cancer (LC) cell line was purchased from Shanghai Biyun Tian Biological Technology Co. Ltd., Shanghai, China, and cultured in RPMI-1640 (Roswell Park Memorial Institute medium 1640) medium supplemented with 10% FBS (v/v) and a combination of penicillin and streptomycin antibiotics (100 U/mL of penicillin and 0.1 g/L of streptomycin). The cells were incubated in a culture chamber at 37°C and under a 5% CO2 atmosphere.

2.2. Transwell Experiment

The Transwell experiment involved culturing well-grown cells in serum-free medium for 24 hours to induce starvation. The matrix gel was mixed until homogeneous using a precooled pipette or pipette tips. The matrix gel was then diluted with serum-free medium to a concentration of 1 mg/mL. A 60 μL volume of the mixture was added vertically into the Transwell chamber. The chamber was incubated at 37°C for 1–3 hours. Following the incubation, 100 μL of serum-free culture medium was added, and the culture plate was placed in a 37°C incubator for 30 minutes to hydrate the gel. The liquid in the chamber was then removed, and the samples were prepared by diluting them with serum-free medium. In a 24-well plate, 500 μL of complete medium containing 10% FBS was added to the lower chamber, and the Transwell chamber was placed inside the wells of the plate using forceps. The starved cells were digested and resuspended in serum-free medium, adjusting the cell density based on the seeding number in the upper chamber. The cell suspension was added to the chamber at a 1 : 1 ratio. The 24-well plate was cultured at 37°C, 5% CO2, and 90% humidity for 24–48 hours. After removing the Transwell chamber, 600 μL of a 4% paraformaldehyde fixation solution was added to a clean well in the 24-well plate, and the chamber was placed in the fixation solution for 30 minutes. Subsequently, 600 μL of crystal violet staining solution was added to the clean well, and the chamber was incubated in the staining solution for 10 minutes. The samples were then subjected to qualitative analysis under a microscope, and 3–5 photographs of different fields were taken for quantitative analysis using ImageJ by counting and averaging the results [33, 34].

2.3. Cell Scratch

To mark the 6-well plates, draw parallel horizontal lines. Next, add 1 × 10^5 cells per well to each of the 6-well plates with 3 replicate wells in each group. Add 2 mL of complete medium to each well, gently blow, and then place them in a 37°C incubator with 5% CO2 overnight (10–12 hours). On the following day, aspirate and discard the medium. Use a 200 μL pipette tip to create a scratch perpendicular to the marker line on the bottom surface of the 6-well plate. After scratching, wash the cells three times with phosphate buffer saline (PBS) to remove any dead cells caused by scratching. Add 3 mL of serum-free medium and place the plates back into the incubator for further incubation. Samples were collected and photographs were taken after 12, 24, and 48 hours to observe the migration of the cells. The cell migration rate was calculated by measuring the widths of the scratches at 0, 12, 24, and 48 hours for the three groups of cells. The experiments were repeated three times and the mean values were obtained [35].

2.4. Network Pharmacology Analysis

The chemical component targets were collected from the PubChem database, and the disease targets were predicted in the GeneCards (https://www.genecards.org/) and OMIM (https://www.omim.org/) databases. The intersection of the two targets was analyzed, and the core protein targets were screened through the protein-protein interaction (PPI) network. Finally, the R package was used to determine the enriched cell components, molecular functions, biological processes, and signaling pathways of the cross-genes. The network pharmacology analysis workflow employed in this study was based on the methodology previously described in publications by our research group [36].

2.5. Molecular Docking Analysis

Molecular docking involves four steps: ligand processing, receptor preparation, docking parameter setup, and analysis and visualization of the output data. For a detailed description of these steps, please refer to the previously published articles by our research group [36]. The parameters associated with the ligand are provided as follows: ACE (PDB ID: 1086, center_x = 40.545 center_y = 37.234 center_z = 43.57 size_x = 40 size_y = 40 size_z = 40). JAK1 (PDB ID: 3eyg, center_x = 10.32 center_y = 4.051 center_z = −16.631 size_x = 40 size_y = 40 size_z = 40). CCR5 (PDB ID: 4 mbs, center_x = 150.317 center_y = 114.851 center_z = 38.968 size_x = 40 size_y = 40 size_z = 40). JAK3 (PDB ID: 5ttu, center_x = −2.894 center_y = 13.627 center_z = −14.612 size_x = 40 size_y = 40 size_z = 40).

2.6. Difference and Survivability Analyses of the Core Proteins

The Gene Expression Profiling Interactive Analysis (GEPIA) website (https://gepia.cancer-pku.cn/) was searched for the core protein after the topology analysis. The disease was set to be lung cancer. The generated analysis diagram was downloaded [37].

2.7. Statistically Treated

SPSS 19.0 statistical software was used for data analysis. The experimental data were expressed as the mean ± standard deviation. The difference between the two groups of data was compared by the t test for statistical analysis. The homogeneity of variance test was carried out to ensure that the variance of the measured results was equal between different groups. For comparison between multiple sets of data, we used a one-way analysis of variance test. was considered statistically significant.

3. Results

3.1. Cell Invasion Test and Cell Scratch

Cell scratch results are shown in Figure 1(a), where the 12 h and 24 h A549 scratches healed significantly less than the control group. This finding demonstrates that the use of scopolamine significantly obstructs the migration of A549 cells. The migration rate of each group was calculated by measuring the scratch width of the three groups of cells at 0, 12, 24, and 48 h. The migration 24 h rate of A549 cells in the control group = 70.42% and the 24 h migration rate of the experimental group = 41.82%. After 48 hours, the A549 control group was completely healed but the experimental group was not healed.

(a)

(b)

(c)

The migration of lung cancer cells was also assessed using the Transwell chamber migration assay. It is worth noting that scopolamine significantly slows down the migration of lung cancer cells (Figures 1(b) and 1(c)). Thus, scopolamine demonstrates an inhibitory effect on the invasion of lung cancer cells.

3.2. Screening of the Drug-Disease Intersection Genes

A total of 314 scopolamine targets were predicted and 2637 lung cancer-related targets were predicted. The identified drug targets were imported into R software with lung cancer, respectively. After cross-analysis, 80 component-disease cross genes were found, respectively (Figure 2).

3.3. PPI Network Construction and Core Gene Screening

The STRING database was employed to preliminarily construct the protein interaction network for the intersection genes obtained in the above step. The string_interactions.txt file obtained from the STRING database was imported into Cytoscape 3.8.0. The Network Analyze plug-in of the software was then used to construct the network, while the Cytonca plug-in was used for the network topology analysis. The key nodes in the network were determined. The screening process is illustrated in Figure 3. Finally, we found that JAK2, JAK3, CCR5, and ACE are the four hub genes of scopolamine affecting lung cancer (Figure 4).

3.4. Potential Target Enrichment Analysis

GO enrichment analysis was performed to characterize the genes based on biological process (BP), molecular function (MF), and cellular component (CC). A significance threshold of was applied, and the results were ranked based on the number of enriched targets, with the top-ranked results selected. In the Biological Process (BP) analysis, the following processes were enriched: cellular calcium ion homeostasis, calcium ion homeostasis, cellular divalent inorganic cation homeostasis, positive regulation of cytosolic calcium ion concentration, response to lipopolysaccharide, and response to antibiotic. In the cellular component (CC) analysis, the following components were enriched: external side of plasma membrane, membrane raft, membrane microdomain, membrane region, postsynaptic membrane, integral component of the presynaptic membrane, and intrinsic component of the presynaptic membrane. In the molecular function (MF) analysis, the following functions were enriched: G protein-coupled peptide receptor activity, peptide receptor activity, drug binding, C-C chemokine receptor activity, C-C chemokine binding, and G protein-coupled receptor activity. Please refer to Figure 5 for more details.

The KEGG pathway analysis revealed several key pathways associated with the impact of scopolamine on lung cancer. These pathways include neuroactive ligand-receptor interaction in cancer, chemokine signaling pathway, necroptosis, PD-L1 expression, and PD-1 checkpoint pathway in cancer, regulation of TRP channel by inflammatory mediators, phenylalanine metabolism, and other signaling pathways. Please refer to Figure 6 for a visual representation of these findings.

3.5. Difference and Survival Analyses of the Core Genes

The Gene Expression Profiling Interactive Analysis (GEPIA) was performed, which generated five core gene correlation analysis figures, depicted in Figure 7. The CCR5 expression, as depicted in the figure, was higher in lung cancer compared to normal cells, while the expressions of ACE, JAK2, and JAK3 demonstrated the opposite trend.

Next, the KM plotter was used. The best thresholds were automatically selected for all parameters. Survival analysis was performed on four hub genes of lung cancer. The results are shown in Figure 8. JAK2, CCR5, and ACE were highly correlated with survival analysis in lung cancer.

(a)

(b)

(c)

(d)

3.6. Molecular Docking of the Core Genes with a Small Molecule and Determination of the Binding Energies of the Docked Complexes

AutoDock Vina was employed for semiflexible docking, and the conformation with the best affinity was selected as the final docking conformation. The conformation with the lowest docking binding energy was selected for the docking binding mode analysis, and the force was analyzed and plotted using PyMoL. The results, as presented in Figure 9, included the following:(a)The ACE-scopolamine action pattern diagram The binding energy of scopolamine to the ACE protein was −7.5 kcal/mol.(b)The JAK2-scopolamine action pattern diagram The binding energy of scopolamine to the JAK2 protein was −7.9 kcal/mol.(c)The CCR5-scopolamine action pattern diagram The binding energy of scopolamine to the CCR5 protein was −7.3 kcal/mol.(d)The JAK3-scopolamine action pattern diagram The binding energy of scopolamine to JAK3 was −6.9 kcal/mol.

(a)

(b)

(c)

(d)

4. Discussion

Surgical intervention is one of the oldest methods in the treatment of lung cancer and remains the most effective approach for managing solid tumors [38–41]. Anesthesia, being a vital component of the perioperative period, has a significant impact on patients’ overall outcomes [37, 42]. In recent years, traditional Chinese anesthesia has gradually showcased its unique advantages and gained widespread utilization in China [43]. Scopolamine, as one of its active ingredients, exhibits marked sedation at low doses and induces hypnosis at higher doses [33]. It is frequently administered as a preanesthetic medication to inhibit glandular secretions and prevent aspiration [17]. Moreover, it exerts a certain degree of central nervous system suppression, making it extensively employed throughout the perioperative period [17, 18]. Compared to other preanesthetic drugs, the use of scopolamine effectively reduces the dosage of anesthetic agents and, consequently, lowers the occurrence of postoperative adverse reactions. Multiple studies have suggested that perioperative anesthesia drugs can have an impact on the viability of tumor cells and significantly influence patient prognosis [44, 45]. In the prescreening drug experiment, this study discovered that scopolamine may possess the capability to inhibit the metastasis of tumor cells.

The results of cell scratch experiments indicated a significant decrease in the healing degree of A549 scratches at 12 h and 24 h postscopolamine administration compared to the control group. This suggests that scopolamine inhibits the migration of A549 cells. Furthermore, Transwell chamber migration assays demonstrated that scopolamine noticeably retards the migration of lung cancer cells, resulting in a substantial reduction in the number of invading cells. As a result, this study concludes that scopolamine exhibits inhibitory effects on lung cancer cells.

Subsequently, we further investigated its potential mechanisms of action through network pharmacology and bioinformatics analysis.

In this study, JAK2, JAK3, CCR5, and ACE were identified as the main targets for the affection of LC based on the property parameters of the core targets. JAK2 (Janus kinase 2): JAK2 is a protein involved in cell signaling pathways that regulate cell growth, differentiation, and survival [46]. Abnormal activation of JAK2 has been implicated in various cancers, including lung cancer. It plays a role in promoting tumor cell proliferation, survival, and metastasis [47]. JAK3 (Janus kinase 3): JAK3 is another member of the Janus kinase family involved in immune cell signaling. While JAK3 mutations have been primarily associated with certain blood cancers, studies have also suggested its involvement in solid tumors, including lung cancer. JAK3 may contribute to tumor growth and progression by influencing immune responses and supporting cancer cell survival [48–50]. CCR5 (C-C chemokine receptor type 5): CCR5 is a protein receptor found on immune cells and is involved in regulating inflammatory responses. Research has shown that CCR5 expression is elevated in lung cancer cells and is associated with increased tumor invasiveness and metastasis. Interaction between CCR5 and its ligands can promote cancer cell migration, invasion, and resistance to apoptosis [51–53]. ACE (Angiotensin-converting enzyme): ACE is an enzyme that plays a crucial role in the renin-angiotensin system, which regulates blood pressure and fluid balance. Studies have suggested a potential link between ACE gene polymorphisms and lung cancer risk, although the evidence is not yet conclusive [54]. ACE inhibitors, medications that inhibit ACE activity, have also been investigated as potential adjuvant therapies for lung cancer due to their anti-inflammatory and antiangiogenic properties [55]. Metastasis is a complex process involving various cellular and molecular events that enable cancer cells to invade surrounding tissues, migrate to distant sites, and establish secondary tumors [56, 57]. The pathways identified in the KEGG analysis play crucial roles in different aspects of metastasis, such as cell adhesion, migration, immune evasion, and angiogenesis. The “neuroactive ligand-receptor interaction in cancer” pathway reflects the importance of neuroactive signaling in tumor progression and metastasis. Dysregulated neurotransmitter signaling can promote cancer cell survival, invasion, and angiogenesis, contributing to metastatic spread [58]. The “PD-1 checkpoint pathway in cancer” is directly associated with immune evasion, which is a critical step in metastasis. The PD-1/PD-L1 interaction can inhibit immune responses against cancer cells, allowing them to evade immune surveillance and establish metastatic lesions [59]. The “chemokine signaling pathway” has been extensively linked to tumor metastasis. Chemokines and their receptors are involved in tumor cell migration, invasion, and recruitment of immune cells to the tumor microenvironment, all of which are important processes in metastasis [60]. Lastly, “PD-L1 expression” is directly related to immune evasion and metastasis. Upregulation of PD-L1 in tumor cells can suppress immune responses and facilitate immune escape, promoting metastatic spread [61]. We performed gene differential analysis, the expression of CCR5 was found to be higher in lung cancer cells compared to normal cells, while ACE, JAK2, and JAK3 showed the opposite trend. These findings indicate a correlation between the expression of these core genes and lung cancer. Furthermore, survival analysis was conducted on the four hub genes in lung cancer patients, revealing a significant correlation between JAK2, CCR5, ACE expression, and patient survival. This supports our hypothesis that scopolamine may suppress lung cancer cell function through modulation of these four core genes. The molecular docking results revealed that scopolamine has the ability to bind effectively to these four proteins, forming stable complexes with each of them. This observation implies that these proteins represent potential drug targets for scopolamine. Furthermore, it indicates that the impact of scopolamine on lung cancer is exerted through the modulation of multiple targets. Overall, by revealing the predicted bindings between scopolamine and proteins involved in lung cancer, it provides important insights into the potential mechanisms of action and therapeutic applications of scopolamine. This knowledge contributes to advancing our understanding of scopolamine’s role in lung cancer treatment and opens up avenues for further research and clinical applications.

Admittedly, there are some limitations in this study. In this study, network pharmacology and bioinformatics methods were used to reveal the mechanism of scopolamine on the migration function of lung cancer cells by constructing a protein interaction network. However, this method is mainly based on the known protein interaction database and gene expression data, and there are limitations in the integrity and accuracy of the database. Therefore, the experimental results may be affected by the deviation or incompleteness of the information in the database. Secondly, this study mainly relies on in vitro cell models for experiments, rather than animal models or clinical experiments. Although in vitro experiments can provide preliminary evidence and mechanism explanation, the results may be different from those in real organisms. Therefore, further animal experiments and clinical studies are necessary to validate these findings and evaluate the potential efficacy of scopolamine in the treatment of lung cancer.

In conclusion, scopolamine demonstrates inhibitory effects on the functioning of lung cancer cells. These effects are mediated through the modulation of multiple targets and pathways, including JAK2, JAK3, CCR5, and ACE. Consequently, this multifaceted approach holds the potential to mitigate the risk of postoperative metastasis and recurrence.

5. Conclusion

JAK2, JAK3, CCR5, and ACE have been identified as the main targets of scopolamine in the treatment of lung cancer. Studies have demonstrated that scopolamine impacts multiple cellular functions in lung cancer cells and may decrease the risk of metastasis. Therefore, it is advisable to administer scopolamine during the preoperative phase for lung cancer patients. Additionally, it is crucial to exploit the inhibitory effects of specific anesthetics on tumor metastasis during clinical anesthesia. Developing individualized and precise anesthetic protocols can effectively reduce the incidence of tumor cell metastasis, thus improving postoperative survival outcomes for patients.

Data Availability

The datasets consulted in the present study are available from the corresponding authors upon reasonable request.

Conflicts of Interest

All authors declare that they have no conflicts of interest associated with the present study.

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Copyright © 2024 Yang Xiao 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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