Dong YD, Wu XM, Liu WQ, Hu YW, Zhang H, Fang WD, Luo Q. Potential mechanism of Camellia luteoflora against colon adenocarcinoma: An integration of network pharmacology and molecular docking. World J Gastrointest Oncol 2025; 17(6): 105782 [DOI: 10.4251/wjgo.v17.i6.105782]
Corresponding Author of This Article
Qing Luo, Laboratory of Cell Engineering of Guizhou Province, Affiliated Hospital of Zunyi Medical University, No. 149 Dalian Road, Huichuan District, Zunyi 563003, Guizhou Province, China. zlsysluoqing@163.com
Research Domain of This Article
Oncology
Article-Type of This Article
Basic Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Yu-Di Dong, Wan-Qing Liu, You-Wu Hu, Hong Zhang, Wan-Di Fang, Qing Luo, The Public Experimental Center of Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi 563003, Guizhou Province, China
Xi-Ming Wu, Department of Periodontics, Suzhou Stomatological Hospital, Suzhou 215005, Jiangsu Province, China
Wan-Qing Liu, You-Wu Hu, Hong Zhang, Wan-Di Fang, Department of Pathology, Affiliated Hospital of Zunyi Medical University, Zunyi 563003, Guizhou Province, China
Qing Luo, Laboratory of Cell Engineering of Guizhou Province, Affiliated Hospital of Zunyi Medical University, Zunyi 563003, Guizhou Province, China
Author contributions: Dong YD and Luo Q designed research; Wu XM and Liu WQ contributed new reagents or analytic tools; Dong YD, Wu XM and Hu YW analyzed data; Zhang H and Fang WD performed visualization; Dong YD wrote the paper; Luo Q and Wu XM reviewed the paper. All authors have read and agreed to the published version of the manuscript.
Supported by Guizhou Provincial Basic Research Program (Natural Science), No. ZK[2023]-554; and the National Natural Science Foundation of China, No. 32360144.
Conflict-of-interest statement: The authors declare no conflicts of interest.
Data sharing statement: The data presented in this study are available on request from the corresponding author due to layout restriction.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Qing Luo, Laboratory of Cell Engineering of Guizhou Province, Affiliated Hospital of Zunyi Medical University, No. 149 Dalian Road, Huichuan District, Zunyi 563003, Guizhou Province, China. zlsysluoqing@163.com
Received: February 7, 2025 Revised: April 1, 2025 Accepted: April 17, 2025 Published online: June 15, 2025 Processing time: 127 Days and 5.5 Hours
Abstract
BACKGROUND
Camellia luteoflora is a unique variety of Camellia in China which is only distributes in Chishui City, Guizhou Province and Luzhou City, Sichuan Province. Its dried leaves are used by local residents as tea to drink with light yellow and special aroma for health care. It has high potential economic medicinal value. Colon adenocarcinoma (COAD) is the third most frequent malignancy and its incidence and mortality is increasing. However, the current common treatments for COAD bring great side effects. In recent years, natural products and their various derivatives have shown significant potential to supplement conventional therapies and to reduce associated toxicity while improving efficacy. In order to overcome the limitations of traditional treatment methods, the global demand and development of natural anti-COAD drugs were increasingly hindered.
AIM
To investigate the potential targets and mechanisms of Camellia luteoflora anti-COAD.
METHODS
Nuclear magnetic resonance and mass spectrometry was used to identified the compounds of Camellia luteoflora. Network pharmacology analysis and survival analysis was used in this study to investigate the anti-COAD effect and mechanism of Camellia luteoflora.
RESULTS
Firstly, a total of 13 compounds were identified. Secondly, 10 active ingredients for 204 potential targets were screened and protein-protein interaction analysis showed that TP53, STAT3, ESR1, MAPK8, AKR1C3, RELA, CYP19A1, CYP1A1, JUN and CYP17A1 were hub targets. GO and KEGG enrichment analyses revealed that Camellia luteoflora exerted anti-COAD effect through multiple functions and pathways. Then, the analysis of survival and stage indicated that TP53 was highly expressed in COAD and the overall survival of high-TP53 and high-CYP19A1 COAD patients was significantly shorter than the low group and there was significant difference in MAPK and RELA expression between different stages. Finally, the molecular docking results demonstrated the binding affinities and sites between active ingredients and TP53, STAT3, ESR1.
CONCLUSION
Our study systematically demonstrated the potential anti-COAD mechanism of Camellia luteoflora and provided a theoretical basis for its further application in the COAD treatment.
Core Tip: Camellia luteoflora is rare and only distributes in Chishui City, Guizhou Province and Luzhou City, Sichuan Province in China, which has high potential economic medicinal value. Natural products and their various derivatives have consistently played a crucial role in anti-tumor drug development. In this study, we aim to explore the active ingredients in Camellia luteoflora and comprehensively identify the pharmacological interaction network of Camellia luteoflora with colon adenocarcinoma.
Citation: Dong YD, Wu XM, Liu WQ, Hu YW, Zhang H, Fang WD, Luo Q. Potential mechanism of Camellia luteoflora against colon adenocarcinoma: An integration of network pharmacology and molecular docking. World J Gastrointest Oncol 2025; 17(6): 105782
Tea is the second most consumed beverage worldwide in recent years. Not only does it taste good, but also has a variety of health benefits. Studies have shown that various ingredients in tea have anti-tumor activities[1,2]. Camellia luteoflora belongs to the Camellia genus, Theaceae family, which is rare and only distributes in Chishui City, Guizhou Province and Luzhou City, Sichuan Province in China[3]. Its dried leaves are used by local residents as tea to drink with light yellow and special aroma for health care. It has high potential economic medicinal value. Due to the scarcity of wild resources, narrow distribution area, human interference and natural factors such as pests and diseases, Camellia luteoflora has been listed as IUCN red list of threatened species-vulnerable species, resulting in the relative lag in basic research on its active ingredients and pharmacology. Camellia plants have a variety of ingredients such as polyphenols, phytosterols, flavonoids, fatty acids, terpenoids and alkaloids which have significant pharmacological effects including anti-tumor, anti-oxidation, anti-inflammatory and immunity enhancement[4-7]. A widely targeted metabolomics analysis of Camellia luteoflora leaves showed that 119 dominant metabolites including oleanolic acid, d-arabitol, eugenol, etc. were obtained and KEGG metabolism pathways were annotated including ABC transporters, the biosynthesis of cofactors, etc[8]. However, there were no pharmacological studies on Camellia luteoflora have been reported.
Colon adenocarcinoma (COAD) is the third most frequent malignancy and the second leading cause of cancer-related death[9]. According to the forecast of International Agency for Research on Cancer, the global incidence rate of COAD will increase 56% from 2020 to 2040, which means there will be more than 3 million COAD cases each year and the mortality will rise to 69%[10]. The trend of increasing incidence and mortality of COAD from year to year is worrying[11]. At present, the treatment of COAD is still mainly surgical resection supplemented with chemotherapy, radiotherapy biological targeted therapy and immunotherapy[12,13]. However, the incidence of third or fourth grade adverse reactions, such as abnormal liver and kidney function, bone marrow suppression, rash, nausea, vomiting, etc., also increased significantly after these treatments[14,15]. In addition, bevacizumab had no significant improvement in adjuvant chemotherapy for stage II/III COAD patients, and it also increased the incidence of arterial vascular events in elderly patients[16]. And cetuximab also showed limitations to individuals with KRAS gene mutation patients. Emerging immunotherapy methods, such as PD-1 inhibitor pembrolizumab showed good therapeutic effect only for COAD with highly microsatellite instability[17]. Therefore, exploring the pathogenesis and finding new therapeutic strategies is of great significance for prolonging the prognosis of COAD patients.
In recent years, natural products and their various derivatives have consistently played a crucial role in anti-tumor drug development, garnering attention from researchers and healthcare professionals alike. Furthermore, they demonstrated remarkable potential in complementing conventional treatments such as radiotherapy and chemotherapy, and enhanced their efficacy while simultaneously reducing the associated toxicity that burdened patients[18,19]. In order to overcome the limitations of traditional treatment methods, the global demand and development of natural anti-tumor drugs were increasingly hindered. Studies have found that Camellia natural products can effectively inhibit colon cancer. For example, Camellia ptilophylla Chang extract significantly induced COAD cell HCT116 mitochondrial apoptosis dependending on the generation of intracellular reactive oxygen species and down-regulation of PI3K/Akt pathway[20]; the transcriptomics and metabolomics analyse indicated that the main bioactive component (-)-Epigallocatechin-3-gallate in Camellia sinensis tea had antitumor activity by inducing cell-cycle arrest, apoptosis and autophagy in HT-29 cells[21].
Despite the potential anti-COAD activity of Camellia, the anti-COAD active components and mechanisms of Camellia luteoflora are still unclear and need to be further explored. To better understand the pharmacological mechanisms, various computational methods were conducted by researchers. Network pharmacology has been widely used in the screening of active ingredients and targets, which was helpful to further study the pharmacological effects of small molecules derived from natural products. Molecular docking confirmed and evaluated the binding ability between the ingredient targets and the disease targets, which verified the prediction results of network pharmacology analysis[22].
In this study, we aim to explore the active ingredients in Camellia luteoflora and comprehensively identify the pharmacological interaction network of Camellia luteoflora with COAD based on network pharmacology analysis, bio-analysis and molecular docking. Our findings demonstrate the potential anti-COAD mechanism of Camellia luteoflora at the molecular level, providing a theoretical basis for its further application in the COAD biomedical treatment field. The complete research process is illustrated in Figure 1.
Figure 1 Network pharmacology regulatory mechanisms of Camellia luteoflora in anti-colon adenocarcinoma.
COAD: Colon adenocarcinoma; PPI: Protein-protein interaction.
MATERIALS AND METHODS
Extraction and identification of ingredients from Camellia luteoflora
Camellia luteoflora was purchased from Chishui Camellia luteoflora Planting Base (Chishui, Guizhou, China). 16 kg dried leaves of Camellia luteoflora were crushed and soaked with its 5 times the volume of 95% ethanol (Shanghai CINC High Purity Solvent Co., Ltd, Shanghai, China). After a week, the extract was collected and concentrated with a rotary evaporator (Büchi Labortechnik AG, Uster, Switzerland) at 50 °C and -0.05Mpa. According to the above methods, the extraction work was repeated for twice (the second and third soaking times were respectively 3 days and 2 days) and finally 2.72 kg crude extract was obtained. Then, the ethyl acetate phase, 1-butanol phase and water phase were extracted and concentrated respectively. The ethyl acetate phase was isolated by silica gel column (Qingdao Kangyexin Medicinal Silicone Co., Ltd, Qingdao, China) and 10 compounds were obtained. The 1-butanol phase was isolated by micro-porous resin (Mitsubishi Chemical Group, Tokyo, Japan) and 3 compounds were obtained. The water phase ingredients were mainly carbohydrates, and small molecular compounds with high purity cannot be separated. In addition, to further identify the compounds in Camellia luteoflora, we preformed mass spectrometry (LCMS-IT/TOF, Shimadzu, Japan) and nuclear magnetic resonance (DRX-500MHz, Bruker, Germany) analysis on the isolated monomer compounds.
Conduction of Camellia luteoflora-targets network
SMILES structures of the small-molecule monomers in Camellia luteoflora were obtained from PubChem database (https://pubchem.ncbi.nlm.nih.gov/) (Supplementary Table 1). Afterward, we imported the SMILES files into the Swiss Target Prediction database (http://swisstargetprediction.ch/) to predicted Camellia luteoflora-related targets. Furthermore, Camellia luteoflora-related targets network was constructed and visualized by using Cytoscape 3.10.2.
Protein-protein interaction network of Camellia luteoflora-COAD targets
A Venn diagram was used to show the intersection targets of Camellia luteoflora and COAD by using Venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/). These intersection targets were imported into the STRING database (https://cn.string-db.org/) to construct the protein-protein interaction (PPI) network of Camellia luteoflora-COAD targets. Organisms was selected as homo sapiens and minimum required interaction score was set to highest confidence 0.9. Cytoscape 3.10.2 was used to calculate the degree value of each target and visualize.
Gene expression differential, survival and stage analyses
GEPIA (http://gepia.cancer-pku.cn/detail.php) is a newly developed interactive web server for analyzing the RNA sequencing expression data of 9736 tumors and 8587 normal samples from the TCGA and the GTEx datasets[23]. In this study, we use the “Box plot” module to analyse the expression of hub genes in COAD and normal colon tissues; the “Survival plot” module to analyse the relationship between the expression levels of hub genes and the prognosis of COAD; the “Stage plot” module to analyse the relationship between the expression level of hub genes and the clinical stage of COAD.
Go and KEGG pathway enrichment analyses
GO enrichment analysis included three categories: Biological process (BP), cellular component (CC) and molecular function (MF). KEGG pathway enrichment analysis indicated the key pathways associated with Camellia luteoflora-COAD targets. Go and KEGG pathway enrichment were analysed by DAVID database and visualized by using an online platform (https://www.bioinformatics.com.cn/)[24].
Molecular docking
The SDF format files of the main active ingredients of Camellia luteoflora were obtained through Pubchem database (https://pubchem.ncbi.nlm.nih.gov/), and structure of the top three proteins with a degree were obtained from the PDB database (https://www.rcsb.org/). Pymol 2.1.0 was used to optimize the target, such as removing water molecules and small molecular ligands and AutoDock Tools 1.5.6 was used for hydrogenation and charge treatment. Pyrx vina 2.0 was used to conduct molecular docking and calculate the binding affinity. This binding ability was represented by the binding affinity (kcal/mol) value, and the lower the affinity value, the more stable the binding ability. Finally, the docking results were further analysed and visualized by using Discovery Studio 2019 Client (https://discover.3ds.com/discovery-studio-visualizer-download).
RESULTS
1H-NMR, 13C-NMR and LC–MS results
In order to isolate and identify the chemical ingredients in the leaves of Camellia luteoflora, its dried leaves were tested by nuclear magnetic hydrogen spectrum and carbon spectrum. The image results of MS were showed in Supplementary Figure 1 and the data were compared with the results of database and published references, a total of 13 ingredients were identified or tentatively characterized respectively, including phytol, β-sitosterol, daucosterol, isoquercitrin, anethole, 1, 2-Di-O-linolenoylglycerol 3-O-β-D-galactopyranoside, chlorogenic acid, cinchonain Ia, cinchonain Ib, methyl chlorogenate, vitexin 2-O-rhamnoside, isovitexin 2-O-rhamnoside and roseoside. The data of compounds such as chemical formula, structural formula (Supplementary Figure 2) and molecular weight were summarized in Table 1.
Table 1 The details of Camellia luteoflora ingredients.
Acquisition of the drug targets and disease targets
By searching the PubChem database and the Swiss Target Prediction database, we obtained 10 active ingredients for 209 potential targets after deleting 71 duplicated targets (Figure 2A). Among the total 13 ingredients, there were no targets matched with cinchonain Ib, cinchonain Ia and methyl chlorogenate, so they were not considered as active ingredients.
Figure 2 Camellia luteoflora-colon adenocarcinoma potential targets and protein-protein interaction network.
A: The 209 potential targets of Camellia luteoflora active ingredients; B: Venn diagram of potential targets prediction; C: The original protein-protein interaction (PPI) network of the interaction targets output by STRING; D: The visualized PPI network of the interaction targets output by Cytoscape; E: The relationship of the top 10 hub genes. COAD: Colon adenocarcinoma.
According to the screening results of the following four databases: DrugBank, GeneCards, OMIM and Therapeutic Target Database, the number of confirmed or potential COAD targets was respectively 40, 24314, 10 and 13. After deleting the duplicates, 24319 targets of COAD were obtained finally.
Camellia luteoflora-COAD potential targets prediction and construction of PPI network
To explore the potential targets of Camellia luteoflora in treating COAD, an intersection analysis was preformed between Camellia luteoflora targets and COAD targets. 204 intersection targets were obtained and visualized by generating a Venn diagram (Figure 2B; Supplementary Table 1). After importing these 204 intersection targets into the STRING database and setting the minimum required intersection score to 0.9, we got a primary PPI network diagram (Figure 2C). There were 204 nodes and 254 edges in the network. Afterward, we import the primary PPI network information into Cytoscape for visualization. As shown in Figure 2D, the higher the degree value of a target, the larger its node size and the darker its node color, indicating that the protein played a more important role in COAD treatment with Camellia luteoflora in intersection with other proteins. The top 10 hub genes, TP53, STAT3, ESR1, MAPK8, AKR1C3, RELA, CYP19A1, CYP1A1, JUN and CYP17A1, were obtained after the intersection of the target genes sorted by the degree and MCC value (Figure 2E; Table 2).
Table 2 Information of top 10 hub genes intersection sorted by degree and Matthews correlation coefficient value.
No.
Gene ID
Degree
MCC
1
TP53
23
173
2
STAT3
14
152
3
ESR1
12
152
4
MAPK8
11
138
5
AKR1C3
11
164
6
RELA
9
131
7
CYP19A1
9
134
8
CYP1A1
9
32
9
JUN
8
138
10
CYP17A1
7
132
Relationship between hub gene expression and the prognosis of COAD patients
To investigate the hub gene expression in COAD and the relationship with the prognosis and stage of COAD patients, gene expression data from 275 COAD and 349 normal colon cases in the TCGA and GTXx database. Compared with the normal groups, the expression of TP53 was significantly increased in the COAD tissues (P < 0.05) but there were no statistically significant differences in the expressions of STAT3, ESR1, MAPK8, AKR1C3, RELA, CYP19A1, and JUN in the COAD tissues (P > 0.05) (Figure 3).
Figure 3 The expression of hub genes in colon adenocarcinoma patients.
Gene expression data from 275 colon adenocarcinoma (COAD) and 349 normal colon cases in the TCGA and GTXx database was used to relationship between the gene expression and the patients prognosis. Compared with the normal groups, the expression of TP53 was significantly increased in the COAD tissues (aP < 0.05) but there were no statistically significant differences in the expressions of STAT3, ESR1, MAPK8, AKR1C3, RELA, CYP19A1 and JUN in the COAD tissues (P > 0.05).
Kaplan-Meier survival curves were plotted to evaluate the relationship between the hub genes (TP53, STAT3, ESR1, MAPK8, AKR1C3, RELA, CYP19A1 and JUN) and the prognosis of COAD patients. In COAD patients with high expression of CYP19A1 and TP53, the overall survival was shorter than that in the lower expression patients which was statistically significant (P < 0.05). But there were no statistically significant differences between patients with high and low expressions of STAT3, ESR1, MAPK8, AKR1C3, RELA and JUN (P > 0.05) (Figure 4).
Figure 4 The relationship of the hub genes with the prognosis of colon adenocarcinoma patients.
Kaplan-Meier survival curves were plotted to evaluate the relationship of the hub genes with the prognosis of colon adenocarcinoma (COAD) patients. The blue line represented the low-expression group, and the red line represented the high-expression group. In COAD patients with high expression of CYP19A1 and TP53, the overall survival was shorter than that in the lower expression patients which was statistically significant [p(HR) < 0.05].
To further investigate the relationship between hub gene expression and clinical stage, we analyzed the gene expression levels in different clinical stages. As shown in Figure 5, there was significant difference in MAPK and RELA expression between stage I, II, II and IV. These results indicated that in the hub Camellia luteoflora-COAD genes, TP53 was highly expressed in COAD tissues and the overall survival of high-TP53 and high-CYP19A1 COAD patients was significantly shorter than the low group and there was significant difference in MAPK and RELA expression between different stages.
Figure 5 The relationship of the hub genes with the stage of colon adenocarcinoma patients.
Violin diagrams were used to represent the relationship of the hub genes with the stage of colon adenocarcinoma patients. Pr (> F) value < 0.05 was considered statistically significant which was red in the figure.
Go and KEGG pathway enrichment analyses
To comprehensively explore the mechanism of the COAD treatment with Camellia luteoflora, GO and KEGG pathway enrichment analyses were performed on the 204 intersection targets. The results of GO enrichment analysis showed that the targets were enriched in 538 BPs, 86 CCs and 152 MFs. According to the p value from low to high, the main GO functions of the targets were illustrated in Figure 6A and B. The top 10 BPs were response to xenobiotic stimulus, adenylate cyclase-activating adrenergic receptor signaling pathway, presynaptic modulation of chemical synaptic transmission, xenobiotic metabolic process, amyloid-beta formation, inflammatory response, response to hypoxia, phospholipase C-activating G protein-coupled receptor signaling pathway, positive regulation of miRNA transcription and intracellular receptor signaling pathway. The top 10 CCs were plasma membrane, presynaptic membrane, synapse, dendrite, endoplasmic reticulum membrane, membrane, neuronal cell body, cell surface, gamma-secretase complex and external side of plasma membrane. The top 10 MFs were nuclear receptor activity, zinc ion binding, enzyme binding, endopeptidase activity, neurotransmitter receptor activity, steroid binding, iron ion binding, heme binding, carbonate dehydratase activity and transcription coactivator binding. The results of KEGG pathway enrichment analysis showed that the targets were enriched in 115 pathways. According to the p value from low to high, the top 10 signaling pathways were neuroactive ligand-receptor interaction, pathways in cancer, steroid hormone biosynthesis, serotonergic synapse, AGE-RAGE signaling pathway in diabetic complications, chemical carcinogenesis-receptor activation, nitrogen metabolism, insulin resistance, sphingolipid signaling pathway and metabolic pathways (Figure 6C and D).
Figure 6 Go function and KEGG pathway enrichment analyses.
A: Bubble plot of GO function enrichment analysis of the key targets; B: Bar plot of GO function enrichment analysis of the key targets; C: Bubble plot of KEGG pathway enrichment analysis of the key targets; D: Sankey diagram of KEGG pathway enrichment analysis of the key targets. BP: Biological process; CC: Cellular component; MF: Molecular function.
Molecular docking
Molecular docking analysis was conducted the potential binding ability between the ten active ingredients of Camellia luteoflora and three target proteins with the highest degree value (TP53, STAT3, ESR1). The molecular docking results showed that the binding affinity ranged from -4.4 kcal/mol to -8.2 kcal/mol (Figure 7A; Table 3). The binding affinity value < -4.25 kcal/mol indicated a certain binding activity, < -5 kcal/mol indicated a better binding activity and < -7 kcal/mol indicated a strong binding activity. According to the criterion, certain binding activity was shown between ten active ingredients of Camellia luteoflora and protein TP53, STAT3, ESR1. For ESR1, chlorogenic acid and isoquercitrin the strongest binding affinities which were -7.8 kcal/mol and -7.7 kcal/mol respectively. For STAT3, daucosterol and isovitexin-2-O-rhamnoside exhibited the strongest binding affinities which were were -7.2 kcal/mol and -7 kcal/mol respectively. For TP53, isovitexin-2-O-rhamnoside and vitrxin-2-O-rhamnoside exhibited the strongest binding affinities which were -8.2 kcal/mol and -7.7 kcal/mol respectively.
Figure 7 Molecular docking analysis of ten active ingredients with TP53, STAT3 and ESR1.
A: Heap map of binding ability between the ten active ingredients and three target proteins (kcal/mol); B: Interaction diagram between ESR1 and chlorogenic; C: Interaction diagram between ESR1 and isoquercitrin; D: Interaction diagram between STAT3 and daucosterol; E: Interaction diagram between STAT3 and isovitexin-2-O-rhamnoside; F: Interaction diagram between TP53 and isovitexin-2-O-rhamnoside; G: Interaction diagram between TP53 and vitrxin-2-O-rhamnoside.
Table 3 Binding affinity of active ingredients to the hub targets.
In order to further explore the specific sites of the binding of these ingredients to ESR1, SAST3 and TP53, the three-dimensional interaction diagrams were conducted. In ESR1, chlorogenic acid formed hydrogen bonds with its amino acid residues VAL534 and ALA350 and hydrophobic interactions with PRO535 charge interactions with ASP351 (Figure 7B); isoquercitrin formed hydrogen bonds with its amino acid residues VAL534 and THR347 and hydrophobic interactions with LEU525, LEU525346, ala350, LEU387 and sulfur-X interactions with MET343 (Figure 7C). In STAT3, daucosterol formed hydrogen bonds with its amino acid residues GLN644, THR641, GLY617 and hydrophobic interactions with ILE653, TYR657, LYS658 and TYR640 (Figure 7D); isovitexin-2-O-rhamnoside formed hydrogen bonds with its amino acid residues GLN247, ARG325, SER513, GLU324, CYS251, PRO333 and hydrophobic interactions with ALA250, PRO256 and electrostatic interactions with ASP334 (Figure 7E). In TP53, isovitexin-2-O-rhamnoside formed hydrogen bonds with its amino acid residues ASN200, THR230, GLU221 and GLY199 and hydrophobic interactions with ILE232 (Figure 7F); vitrxin-2-O-rhamnoside formed hydrogen bonds with its amino acid residues THR256, LEU264, GLU258, GLY262, ARG158, SER99 and hydrophobic interactions with PRO98, LEU264 (Figure 7G).
DISCUSSION
The incidence of COAD is increasing years by years in the worldwide with the improvement of living standards. Due to the development of the treatment of COAD behind the disease, the 5-year survival rate of the metastatic patients is still less than 10%[25]. Network pharmacology was utilized in this study to investigate the underlying mechanism of Camellia luteoflora in the treatment of COAD known for its multi-ingredients and multi-target characteristics. The PPI network of Camellia luteoflora-COAD targets indicated that TP53, STAT3, ESR1, MAPK8, AKR1C3, RELA, CYP19A1, CYP1A1, JUN and CYP17A1 shown significance. Consequently, the relationship of these hub genes with the prognosis and stage of COAD was analyzed. The isolation and identification of chemical ingredients in plant materials is of great significance in the field of natural product research[26]. Currently, various analytical techniques are employed for this purpose. In this regard, NMR and LCMS are commonly used methods. This study is the first to isolate and identify the chemical ingredients of Camellia luteoflora, which helps to further understand the chemical components of oil tea, and has potential guiding significance in natural products against COAD fields.
The survival analysis conducted in this study highlighted the critical role of specific hub genes in COAD patients. Notably, the significant differences in overall survival associated with the expression levels of CYP19A1 and TP53 underscored their potential as prognostic biomarkers. TP53, a well-established tumor suppressor gene, was frequently mutated in various tumors and its loss of function was often correlated with poor clinical outcomes. Early studies established TP53-medicated cell cycle arrest, apoptosis and DNA damage as the classic barriers in tumor development. With the deepening of research on TP53, more and more studies have shown that TP53 was also closely related to tumor metabolism[27,28], ferroptosis[29,30], stem cell dynamic[31,32], cell competition[33,34], epithelial-mesenchymal transition[35,36] and immunity[37,38]. CYP19A1, a member of cytochrome P450 family, was a key enzyme in converting androgens to estrogens in the process of estrogen biosynthesis. The high expression of CYP19A1 had been implicated in the modulation of estrogen levels in the tumor microenvironment, potentially influencing tumor progression[39-41]. Together with previous studies, our findings indicated that TP53 and CYP19A1 expression were important prognostic indicators in COAD, implying that targeting TP53 and CYP19A1 as a treatment for COAD remained enticing approaches to pursue. Conversely, the lack of statistically significant differences in overall survival associated with the expression of STAT3, ESR1, MAPK8, AKR1C3, RELA, and JUN indicated that these genes may not play a direct role in the prognosis of COAD patients, at least within the context of this study. We hypothesized that these genes might be involved in other BP but not correlated with prognosis in COAD, so further investigations were necessary to explore the roles and mechanisms of these genes in COAD. The clinical stage analysis showed that there were significant differences in MAPK and RELA expressions between COAD stage I, II, II and IV. In summary, future studies should focus on validating these findings in larger cohorts and exploring the functional implications of these genes in the progression and treatment response of COAD.
GO and KEGG pathway enrichment analyses revealed the key function and pathways involved in the treatment of Camellia luteoflora. GO enrichment analysis indicated that the hub targets of Camellia luteoflora were enriched in BP such as adenylate cyclase-activating adrenergic receptor signaling pathway and phospholipase C-activating G protein-coupled receptor signaling pathway. KEGG pathway enrichment analysis suggested that Camellia luteoflora might be through the several pathways in the treatment of COAD, including neuroactive ligand-receptor interaction, steroid hormone biosynthesis and metabolic pathways. A silico study suggested that inhibition of neuroactive ligand-receptor interaction pathway can enhance immunotherapy response in colon cancer[42]. Steroid hormone included estrogen, androgen and adrenocortical hormone. Interestingly, estrogen and androgen respectively reduced and increased the risk of colorectal cancer by regulating antitumor immune responses[43]. Various metabolic pathways such as glucose metabolism[44], lipid metabolism[45] and glutathione metabolism[46] were closely related to COAD. These findings holed significant potential for the strategic purposing of Camellia luteoflora and promised advancements in COAD therapies.
Moreover, molecular docking was used to explore the binding affinity and mechanisms of Camellia luteoflora with key COAD-related targets. The results showed that 10 active ingredients of Camellia luteoflora and top 3 target proteins all had a certain binding activity. Among them, TP53 and isovitexin-2-O-rhamnoside had the strongest binding activity, primarily driven by hydrogen bonds and hydrophobic interactions. Approximately 60% COAD patients had TP53 mutations which was closely associated with tumorigenesis and progression[47]. Studies had found that COAD patients with TP53 mutation have shown high heterogeneity, so individual treatment for these patients was of great clinical significance[48]. Our study may provide new therapeutic strategies for TP53-targeted COAD therapy.
In summary, this study used network pharmacology to predict active ingredients and key targets and pathways associated with anti-COAD effects of Camellia luteoflora. Furthermore, the hub genes expression in COAD and the relationship with the prognosis and stage of COAD patients was conducted by bioinformatics analysis. Moreover, molecular docking analysis was conducted the potential binding ability between the ten active ingredients of Camellia luteoflora and top three targets. These findings supported that Camellia luteoflora had great potential in the treatment of COAD which providing strong evidence for further research. However, this study has certain limitations. At present, we are conducting a preliminary study on the effects of Camellia luteoflora on the proliferation, invasion and migration of COAD in vitro. In the subsequent verification experiments, we will explore the effect and mechanism of Camellia luteoflora on COAD proliferation, invasion, migration and drug-resistance in vitro and in vivo and investigate the direct target based on the molecular docking results, aiming to provide insight treatments and research basis for the clinical treatment of COAD patients.
CONCLUSION
Our study systematically demonstrated the potential anti-COAD mechanism of Camellia luteoflora and provided a theoretical basis for its further application in the COAD treatment.
ACKNOWLEDGEMENTS
We would like to express our sincere gratitude to Chishui Camellia luteoflora Planting Base for providing Camellia luteoflora and for their invaluable technical support.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Oncology
Country of origin: China
Peer-review report’s classification
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P-Reviewer: Gholam GM; Li XX; Tang XH S-Editor: Qu XL L-Editor: A P-Editor: Zhao YQ
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Wang Z, Hou X, Li M, Ji R, Li Z, Wang Y, Guo Y, Liu D, Huang B, Du H. Active fractions of golden-flowered tea (Camellia nitidissima Chi) inhibit epidermal growth factor receptor mutated non-small cell lung cancer via multiple pathways and targets in vitro and in vivo.Front Nutr. 2022;9:1014414.
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Yang W, Liu F, Wu G, Liang S, Bai X, Liu B, Zhang B, Chen H, Yang J. Widely Targeted Metabolomics Analysis of the Roots, Stems, Leaves, Flowers, and Fruits of Camellia luteoflora, a Species with an Extremely Small Population.Molecules. 2024;29.
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Zhou Q, Lei L, Cheng J, Chen J, Du Y, Zhang X, Li Q, Li C, Deng H, Wong CC, Zhuang B, Li G, Bai X. Microbiota-induced S100A11-RAGE axis underlies immune evasion in right-sided colon adenomas and is a therapeutic target to boost anti-PD1 efficacy.Gut. 2025;74:214-228.
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Zhu M, Kim J, Deng Q, Ricciuti B, Alessi JV, Eglenen-Polat B, Bender ME, Huang HC, Kowash RR, Cuevas I, Bennett ZT, Gao J, Minna JD, Castrillon DH, Awad MM, Xu L, Akbay EA. Loss of p53 and mutational heterogeneity drives immune resistance in an autochthonous mouse lung cancer model with high tumor mutational burden.Cancer Cell. 2023;41:1731-1748.e8.
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