Network Pharmacology,Molecular Docking,and Experimental Validation to Investigate the Mechanism of Qifu Longkui Decoction in the Treatment of Colorectal Cancer

Abstract

Objective

This study aimed to validate the potential targets of QLD for treating CRC and explore its possible therapeutic mechanism through network pharmacology, molecular docking, and experimental validation.

Methods

The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), the Traditional Chinese Medicine Information Database (TCMID), a literature search, and the SwissTargetPrediction database were used to identify the active components and potential targets of QLD. The Online Mendelian Inheritance in Man (OMIM), GeneCards, and DrugBank databases were utilized for CRC target identification. Common targets in CRC and QLD were subsequently screened via a Venn diagram. Next, the Search Tool for the Retrieval of Interacting Genes/Genomes (STRING) database was used to perform protein-protein interaction (PPI) network analysis of the common targets. Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were employed to identify signaling pathways. After that, “drug-component-target” networks were built via Cytoscape 3.9.1 [2024.3.2]. AutoDock Tools 1.5.7 [2024.4.6] and PyMoL 2.4.0 [2024.4.13] were utilized for molecular docking to analyze the relationships between the active ingredients and core targets. Later, in vitro experiments were performed to validate the anticancer effects of QLD on CRC.

Results

Network pharmacology analysis revealed 200 active components and 194 potential targets of QLD from the TCMSP database. Disease target databases predicted 1590 targets associated with CRC. The potential anti-colorectal cancer mechanism of QLD may involve lipid and atherosclerosis, chemical carcinogenesis-receptor activation, HIF-1 signaling pathway, TNF signaling pathway, cellular senescence, EGFR tyrosine kinase inhibitor resistance, platinum drug resistance, and the FoxO signaling pathway. Furthermore, QLD has a therapeutic effect through its effects on the 6 core targets TP53, AKT1, TNF, EGFR, IL6 and CASP3. Kaempferol is an active ingredient of QLD and is a flavonoid compound that is known for its antitumor, antioxidant and anti-inflammatory effects. It is unclear how kaempferol affects the onset of CRC.¹ In this study, when the concentration of kaempferol was 2 mg/mL, the proliferative capacity of colorectal cancer cells was inhibited, and kaempferol regulated the AKT/CyclinD1 pathway to inhibit the proliferation of Caco-2 cells.

Conclusions

Network pharmacology approaches in cancer therapy are highly beneficial.² This approach serves as an effective supplementary method for identifying multiple targets of QLD and the underlying mechanisms involved in the fight against CRC. This research reveals the potential role of QLD in the treatment of CRC from a network pharmacology perspective for the first time, enhances the knowledge regarding QLD and offers new insight into QLD research for CRC treatment.

Keywords

Qifu Longkui Decoction (QLD)colorectal cancer (CRC)molecular docking network pharmacology kaempferol

Introduction

Colorectal cancer (CRC) is a common malignant tumor of the gastrointestinal tract with atypical early symptoms that can manifest as dyspepsia. With the progression of cancer, systemic symptoms appear. When infiltration and metastasis to vital organs occur, different clinical symptoms appear. The exact cause of CRC remains unknown, but it includes malignant changes in benign intestinal tumors, dietary practices, polyps, inflammatory stimuli, and genetic and pharmaceutical factors.³ Chemotherapy is often combined with radiotherapy and targeted therapy to treat advanced CRC. Adverse effects include gastrointestinal reactions, bone marrow suppression, and impaired liver functions.⁴ Patients are generally unable to tolerate adverse effects; therefore, it is necessary to explore the combination of CRC treatment with traditional Chinese medicine (TCM) to reduce toxic side effects and improve survival quality. In Chinese medicine diagnosis, CRC occurs due to poor qi and blood circulation, deficiency of the spleen and kidney, stagnation of dampness, heat, and toxicity.⁵ Recently, herbal medicine has attracted increased interest because of its potential to reduce toxicity and its multiple targets. Studies have shown that Chinese medicine induces apoptosis and autophagy, inhibits metastasis, and influences the immune response after the treatment of lung cancer.⁶ The inhibition of the proliferation and migration of CRC cells by TCM has been reported previously.⁷ In cancer therapies, TCM has been reported to be effective in alleviating adverse gastrointestinal reactions to radiotherapy and chemotherapy, reducing the incidence of myelosuppression and attenuating cardiotoxicity. These findings help to understand TCM as an important adjuvant therapy for cancers.⁸ Qifu Longkui Decoction (QLD) is a Chinese herbal formula. It consists of 13 species of TCM, including Danshen (Salvia miltiorrhiza Bunge), Fuzi (Aconitum carmichaelii Debx.), Ganjiang (Zingiber officinale Roscoe), Huangqi (Astragalus mongholicus Bunge.), Longkui (Solanum nigrum Linn), Shichangpu (Acori Tatarinowii Rhizoma), Xianhecao (Agrimonia pilosa Ledeb.), Yujin (Curcuma aromatica Salisb.), Fuling (Smilax glabra Roxb.), Shanzhuyu (Cornus officinalis Sieb. et Zucc.), Baishao (Paeonia lactiflora Pall.), Chenpi (Pericarpium Citri Reticulatae) and Buguzhi (Psoralea corylifolia Linn.). QLD is used to treat colorectal cancer in China, and it effectively reduces serum vascular endothelial growth factor levels and improves immune function. The efficacy of QLD is to remove blood stasis, relieve dampness and dispel phlegm, warm yang and qi, clear away heat and nourish yin, which is in line with the characteristics of the pathogenesis of CRC. The pathogenesis of CRC involves the invasion of evil qi and coagulation of qi, blood and fluid, resulting in intestinal dysfunction for a long period of time and eventually the development of tumors.⁹ QLD is a combination chemotherapeutic agent used to treat CRC. When QLD was combined with a chemotherapy regimen for the treatment of advanced CRC, the effective rate of the observation group was higher than that of the control group. QLD can inhibit the proliferation of tumor cells, improve patient immunity, and enhance tolerance to the toxic side effects of chemotherapy.¹⁰ Clinical studies have demonstrated the adjuvant role of QLD in the treatment of advanced and metastatic CRC, and QLD effectively reduces serum vascular endothelial growth factor levels and improves immune function and survival quality.¹¹ This study applied network pharmacology to predict possible relevant targets for QLD in treating CRC, active components, and signaling pathways, and the predictions were verified through molecular docking and experimentation. In addition, relatively few studies have investigated kaempferol, and its mechanisms of action in the inhibition of CRC cell proliferation have been explored. The strategy for the main research components employed in this study is shown in Figure 1.

Figure 1.

Schematic workflow of the study.

Materials and Methods

Network Pharmacology

Screening of Active Ingredients and Targets of QLD

The active chemical components in the QLD were obtained from the systematic Pharmacology Database of Traditional Chinese Medicine (TCMSP) (https://old.tcmsp-e.com/tcmspsearch.php).¹² Oral bioavailability (OB) refers to the percentage of the oral dose of Chinese herbal medicines that are absorbed by the gastrointestinal tract into the circulating blood. Drug-likeness (DL) refers to the drug-like properties of a compound. We referred to the TCMSP database for the recommended inclusion criteria for oral herbal medicines. To select potential ingredients and their targets, oral bioavailability (OB) ≥ 30% and drug-likeness (DL) ≥ 0.18 were set as screening conditions. In particular, Buguzhi (Psoralea corylifolia Linn.) is one of the herbs of QLD, and since Buguzhi could not be identified in the TCMSP database, other databases were utilized to obtain compositional targets. The chemical constituents of Buguzhi were acquired from the Traditional Chinese Medicine Information Database (TCMID) (https://bidd.group/TCMID/index.html) and were further screened on the basis of the absorption, distribution, metabolism, and excretion (ADME) parameters.¹³ The UniProt database (https://www.UniProt.org/) standardizes the target into human genes.¹⁴

Collecting the CRC Targets

CRC targets were predicted by integrating the data and deleting duplicates from the GeneCards(https://www.GeneCardss.org/),¹⁵ OMIM(https://www.omim.org/), and DrugBank (https://go.DrugBank.com/) databases.^16,17

Construction of the “Herb-Ingredient-Target” Network

Common targets of the active ingredients of QLD and CRC are shown in a Venn Diagram (https://bioinformatics.psb.ugent.be/webtools/Venn/), and these targets were used to construct a QLD-ingredient-target network with the active ingredients via Cytoscape 3.9.1 (http://www.Cytoscape.org/) software.¹⁸ Before being imported into Cytoscape software, two files are prepared: the first is the network file with two columns of data of herbs and the common targets mentioned above, and the second is the type file with two columns of data of items and attributes. The attributes are entered to summarize items, the formats of the nodes are adjusted, and a “herb-ingredient-targets” network diagram is drawn.

Enrichment Analysis

GO and KEGG pathway enrichment analyses were performed for the common targets via the Metascape database (https://metascape.org/gp/index.html).^19,20 The top 20 terms were subsequently selected to obtain the QLD biological processes and signaling pathways associated with CRC, which are presented in bubble and bar graphs, respectively. These bubble and bar graphs were generated via bioinformatics (https://www.bioinformatics.com.cn/login/).

Molecular Docking

Molecular docking is a method that focuses on the study of intermolecular (ligand-receptor) interactions and the prediction of binding modes and binding capacity. In recent years, it has become an important technology in the field of computer-aided drug discovery. The common targets were selected on the basis of maximal clique centrality (MCC), degree, edge percolated component (EPC), closeness, and complementarity in Cytoscape 3.9.1. The top 20 targets were selected for each criterion and analyzed to obtain the common target genes. Furthermore, the genes were screened by degree, and the resulting top 7 targets were chosen as the final core targets to determine their corresponding active ingredients in the QLD herbal ingredients for molecular docking.

Experimental Validation

Preparation of Kaempferol

The extract of the QLD kaempferol (purity: 99.86%, CAS No. 520-18-3; MedChemExpress, China) was dissolved in dimethyl sulfoxide at a concentration of 20 mg/mL and stored at −20 °C.

Cell Culture

The Caco-2 cell line was cultured in RPMI-1640 medium supplemented with 10% fetal bovine serum (FBS) (Gibco, United States) and 1% penicillin/streptomycin at 37 °C with 5% carbon dioxide (CO₂).

Cell Proliferation

Caco-2 cells were inoculated in 96-well plates at 3000 cells/well and cultured overnight. Then, the cells were treated with different concentrations of kaempferol for 0, 24, 48, or 72 h. After adding the Cell Counting Kit-8 (CCK-8) reagent diluted with complete medium and incubating at 37 °C for 4 h, the optical density (OD) value was measured at 450 nm via an enzyme labeler.

Cell Migration

A wound-healing assay was used to assess the inhibitory effect of QLD on the migratory ability of CRC cells. Caco-2 cells were inoculated in 6-well plates at 5 × 10⁵ cells/well, followed by overnight cell spreading. Then, the cells were uniformly scratched with a pipette tip and washed 3 times with phosphate-buffered saline (PBS) to remove cell debris. Serum-free medium containing different concentrations of kaempferol was used for culture at 37 °C with 5% CO₂ for 48 h. Photographs were captured via a microscope, and the results were statistically analyzed.

Colony Formation Assay

Caco-2 cells were inoculated in 6-well plates at 500 cells/well and allowed to adhere to the plate. The cells were then treated with different concentrations of kaempferol for 24 h, followed by a switch to complete medium and additional incubation for 2 weeks. After this, the colonies were fixed with 4% paraformaldehyde for 30 min and stained with 0.1% crystal violet solution for 30 min. The colonies were examined under a light microscope and counted manually in three randomly selected fields to determine the number of colonies.

Western Blot

The experimental study followed standard operating procedures.²¹ Primary antibodies against the following proteins were used: AKT (#4691, Cell Signaling Technology, United States), CyclinD1 (ab6152, Abcam, Britain), and GAPDH (TA-08, ZSGB-BIO, China). The secondary antibodies used were HRP-conjugated goat anti-mouse IgG (H + L) (AS003, ABclonal, China) and HRP-conjugated goat anti-rabbit IgG (H + L) (AS014, ABclonal, China).

Statistical Analysis

All the statistical analyses were performed using GraphPad Prism 9 software. Student's t tests and one-way ANOVA were used to compare two or more groups. The experimental results are presented as the means ± SD; P < 0.05 was considered a statistically significant difference.

Results

Collection of QLD Active Ingredients and CRC Targets

The main elements of this study are depicted in Figure 1. Buguzhi was entered into the TCMID database, resulting in 33 chemical compositions. These compositions were subsequently used to predict the targets of Buguzhi in the Swiss Target Prediction database. The remaining herbs were entered into the TCMSP database with the parameters set at OB ≥ 30% and DL ≥ 0.18, which identified 167 active ingredients in the database. Overall, a total of 194 targets corresponding to active ingredients were obtained after removing duplicates. A systematic search of the GeneCards, OMIM, and DrugBank databases revealed 1590 CRC targets after removing duplicates.

Obtaining Potential Targets of QLD for Treating CRC

Mapping of the QLD active ingredient targets and CRC targets through the Draw Venn diagram platform revealed 147 intersecting targets (Figure 2A). These intersecting targets are regarded as potential targets for QLD for the treatment of CRC. The STRING database generated protein–protein interaction (PPI) network maps of intersecting targets (Figure 2B). The PPI network diagram was subsequently imported into Cytoscape 3.9.1 software, followed by the arrangement and distribution of intersecting targets according to the degree value to prepare for the next step of screening core targets (Figure 2C).

Figure 2.

PPI network of QLD and CRC. (A) Venn diagram of intersecting targets of QLD and CRC; (B) PPI generated by String database; and (C) Distribution of intersecting targets by degree value determined by Cytoscape 3.9.1 software. (D) Representation of the “herb-ingredient-target” network of QLD.

Construction of the “Herb-Ingredient-Target” Network

To analyze and process active ingredients, potential targets with active ingredients were combined and imported into Cytoscape 3.9.1 software. The blue rectangle represents the herbal component of QLD. The different colored ellipses, left to right and top to bottom, are the active ingredients of Danshen, Fuzi, Ganjiang, Huangqi, Longkui, Shichangpu, Xianhecao, Yujin, Fuling, Shanzhuyu, Baishao, Chenpi and Buguzhi. Table S1 shows the authoritative names of these 13 herbs. The blue rectangles on both sides (A1–G1) illustrate the common components of some of these herbs (Table S2). A1 is sitosterol, which is a common component of Baishao, Chenpi, Fuzi, Ganjiang, Longkui, Yujin, and Shanzhuyu; B1 is quercetin, which is a common component of Huangqi, Longkui, and Xianhecao; C1 is kaempferol, which is a common constituent of Baishao, Huangqi, Shichangpu, and Xianhecao; thus, one-third of all the herbs in the QLD contain kaempferol; D1 is beta-sitosterol, which is a common component of Baishao, Ganjiang, Yujin, and Shanzhuyu; E1 is luteolin, which is a common representative component of Danshen and Xianhecao; F1 is naringenin, which is a common component of Chenpi and Yujin; and G1 is catechin, which represents a common component of Baishao and Xianhecao. The orange rectangle in the center depicts the potential targets (Figure 2D).

GO and KEGG Enrichment Analysis of Intersecting Targets

In the Metascape 3.9.1 database, 147 intersecting targets were imported for GO and KEGG enrichment analysis to determine the critical biological function of QLD for CRC treatment. On the basis of the results of the GO analysis, the top 20 biological process (BP), cellular composition (CC), and molecular function (MF) terms were assigned for further studies. BP was associated primarily with the response to hormones, the response to xenobiotic stimuli, positive regulation of cell migration, cell population proliferation, and regulation of the inflammatory response (Figure 3A). The MF terms included transcription factor binding, protein kinase activity, cytokine activity, protease binding and antioxidant activity (Figure 3B). The CC mainly consists of membrane rafts, receptor complexes, vesicle lumens, spindles and germ cell nuclei (Figure 3C). KEGG analysis revealed that the intersecting targets were enriched mainly in pathways related to cancer, lipid and atherosclerosis; chemical carcinogenesis-receptor activation; the HIF-1 signaling pathway; the TNF signaling pathway; cellular senescence; EGFR tyrosine kinase inhibitor resistance; platinum drug resistance; and the FoxO signaling pathway (Figure 3D).

Figure 3.

Go function and KEGG pathway enrichment analysis. (A) BP; (B) MF; (C) CC; (D)KEGG enrichment analysis. (E) Intersection analysis of the top 20 core genes derived from protein-protein interaction analysis.

Protein-Protein Interaction Network Construction

Intersecting targets of QLD and CRC were imported into the STRING database for analysis and to construct the PPI network between QLD and CRC. The results were imported into Cytoscape 3.9.1 software in the tsv format, and the top 20 core genes representing each metric based on cytoHubba's “MCC,” “Degree,” “EPC,” “Closeness,” and “Radiality” were selected. The intersection from this set of 5 dimensions is then used to obtain 16 key targets. A total of 16 key targets were identified and arranged in descending order of degree: TP53, AKT1, ALB, TNF, EGFR, IL6, CASP3, ESR1, STAT3, BCL2, HIF1A, CTNNB1, MYC, MMP9, PTGS2, IL1B, and PTEN (Table 1). The intersection was taken from the target genes in the five options (Figure 3E).

Table 1.

Top20 Core Genes Obtained from CytoHubba Screening.

Rank	MCC	Degree	EPC	Closeness	Radiality
1	BCL2	TP53	TP53	TP53	TP53
2	HIF1A	AKT1	AKT1	AKT1	AKT1
3	ALB	ALB	IL6	ALB	ALB
4	MMP9	TNF	ALB	TNF	TNF
5	IL6	EGFR	TNF	EGFR	EGFR
6	TNF	IL6	STAT3	IL6	IL6
7	STAT3	CASP3	HIF1A	ESR1	ESR1
8	CASP3	ESR1	BCL2	STAT3	STAT3
9	AKT1	STAT3	EGFR	CASP3	CASP3
10	TP53	BCL2	ESR1	BCL2	BCL2
11	PTGS2	HIF1A	CTNNB1	HIF1A	HIF1A
12	CTNNB1	CTNNB1	MYC	CTNNB1	MYC
13	EGFR	MYC	CASP3	MYC	CTNNB1
14	MYC	MMP9	MMP9	MMP9	PTGS2
15	IL1B	PTGS2	IL1B	PTGS2	MMP9
16	ESR1	IL1B	MAPK3	IL1B	IL1B
17	IFNG	PPARG	PTEN	PPARG	PPARG
18	CXCL8	MAPK3	PPARG	MAPK3	PTEN
19	PTEN	PTEN	PTGS2	PTEN	MAPK3
20	NFKBIA	CCND1	GSK3B	CCND1	ERBB2

Molecular Docking Analysis

Table 2 summarizes the molecular docking of the 6 core targets and the 7 main active ingredients. Figure S1 shows the chemical structures of the main active ingredients. Three-dimensional schematics of the docking results were obtained via PyMoL software. In this study, one of the core targets, ALB, and one of the main active ingredients, beta-carotene, could not be molecularly docked due to structural issues. The larger the absolute value of the binding energy is, the stronger the interactions between the molecules and the more stable the structure. Figure 4A shows the docking results between diosgenin, luteolin, nobiletin, and quercetin with the TP53 receptor. Additionally, all four compounds strongly interact with TP53, and their nucleophilicity is in the order of luteolin > diosgenin > nobiletin > quercetin. Furthermore, their potential binding sites were identified as TYR-1600, ASN-1498, ASP-1521, TYR-1500, ARG-1490, ASP-1531, LEU-1528, and SER-1496. All four compounds form at least one hydrogen bond with an amino acid residue. Figure 4B shows the docking results between quercetin, kaempferol, diosgenin, luteolin, and naringenin and the AKT1 receptor. In this case, the nucleophilicity of these five compounds is in the order of diosgenin > naringenin > luteolin > quercetin > kaempferol. The potential binding sites are GLY-393, ARG-465, GLU-464, HIS-220, PRO-427, LEU-213, SER-205, ILE-366, GLU-397, and ARG-406. In this case, all five compounds form at least one hydrogen bond with an amino acid residue. Figure 5A shows the docking results between kaempferol, luteolin, cryptotanshinone, and quercetin with TNF receptor. The nucleophilicity of these compounds is in the order of cryptotanshinone > luteolin > kaempferol > quercetin. The potential binding sites are mainly GLN-102, GLU-110, GLU-116, ASN-112, and ARG-103. All four compounds form at least one hydrogen bond with an amino acid residue. The molecular docking of two components (quercetin and luteolin) was performed with 3 core targets (EGFR, IL6, and CASP3). The docking results of quercetin and luteolin with the EGFR, IL6, and CASP3 receptors are presented in Figure 5B, Figure 5C, and Figure 5D, respectively. Both compounds have relatively good nucleophilicity toward these three core targets.

Figure 4.

Validation of molecular docking. (A) Molecualr interaction of TP53 binds with diosgenin; luteolin; nobiletin and quercetin. (B) Molecular interaction of AKT1 binds with quercetin; kaempferol; diosgenin; luteolin and naringenin.

Figure 5.

Validation of molecular docking. (A) Docking analysis of TNF binds with kaempferol; luteolin; cryptotanshinone and quercetin. (B) Molecular interaction of EGFR with quercetin and luteolin. (C) Docking analysis of IL6 binds with quercetin and luteolin. (D) Molecular interaction of CASP3 with quercetin and luteolin.

Table 2.

Molecular Docking Analysis Results of 6 Core Targets and Correlated Active Ingredient.

Target	Entry	PDB ID	Molecular name	Docking score (kcal/mol)
TP53	Q12888	8swj	quercetin	−4.9
			diosgenin	−5.57
			luteolin	−5.99
			nobiletin	−5.47
AKT1	P31749	3cqw	quercetin	−5.38
			kaempferol	−4.69
			diosgenin	−8.21
			luteolin	−5.71
			naringenin	−5.95
TNF	P01375	2e7a	kaempferol	−6.46
			luteolin	−6.56
			cryptotanshinone	−7.71
			quercetin	−5.69
EGFR	P00533	2rgp	quercetin	−6.49
EGFR	P00533	2rgp	luteolin	−5.67
IL6	P05231	1alu	quercetin	−5.21
IL6	P05231	1alu	luteolin	−4.98
CASP3	P42574	4sp0	quercetin	−5.67
CASP3	P42574	4sp0	luteolin	−7.1

Kaempferol Inhibits the Proliferation of Colorectal Cancer Cells

On the basis of the docking analysis between the active ingredients and core target molecules, among the 7 main active ingredients in molecular docking, kaempferol ranked second in degree value (Table S3). These results suggest that kaempferol is an important ingredient and is valuable for our research. This study aimed to evaluate the effect of QLD on the proliferation of CRC cells. Then, Caco-2 CRC cells were treated with different concentrations of kaempferol to determine the impact of kaempferol on the proliferative capacity of CRC cells via CCK-8 and colony formation assays. Figure 6A shows the inhibitory effect of kaempferol on colorectal cell proliferation in a time- and dose-dependent manner. Similarly, as shown in Figure 6B, kaempferol inhibited both the proliferation and colony-forming ability of CRC cells in a dose-dependent manner.

Figure 6.

Kaempferol affects the proliferation of colorectal cancer cells. (A) Caco-2 cells were treated with different concentrations of kaempferol for 0,24,48 and 72 h, using a CCK-8 kit to detect cellular activity; (B) Caco-2 cells were treated with different concentrations of kaempferol, exploring colony-forming ability. (C) The migration capability was measured after being treated with different concentrations of kaempferol. (D) Effects of various concentrations of kaempferol on AKT/CyclinD1 pathway protein expression in colorectal cancer cells.

Kaempferol Inhibits the Migration of Colorectal Cancer Cells

A wound-healing assay was used to explore the effects of different concentrations of kaempferol on the migratory ability of CRC cells. Figure 6C shows the dose-dependent inhibition of CRC migratory ability in the kaempferol-treated group compared with the control group. The experimental results confirmed that kaempferol inhibited the migratory ability of CRC cells.

Kaempferol Regulates the AKT/Cyclin D1 Pathway to Inhibit the Proliferation of Colorectal Cancer Cells

Cell function experiments demonstrated the potential of QLD to inhibit CRC cell proliferation. In this study, AKT was the primary target, whereas CyclinD1 is an important cell cycle regulator that plays a central role in cancer pathogenesis. The AKT/cyclin D1 pathway has been shown to affect cancer cell proliferation. Further investigation of the role of this pathway in CRC, in conjunction with the results of this study, involved detecting pathway protein expression after kaempferol treatment via western blotting. As depicted in Figure 6D, an increase in kaempferol concentration resulted in a decrease in the protein expression levels of AKT and CyclinD1.

Discussion

According to the WHO Global Cancer Statistics Report 2020, CRC accounts for 10% of all cancers, with the third-highest incidence rate and the second-highest mortality rate.²² Currently, CRC is treated primarily with surgical adjuvant therapies, including radiotherapy, chemotherapy, and immunotherapy. Since these treatment strategies show large variations in treatment efficacy among different patients, there is a risk of recurrence and metastasis.²³ Therefore, additional treatment modalities must be explored for patients who cannot tolerate the abovementioned treatment strategies to improve survival and prognosis. The development and application of network pharmacology have facilitated research toward establishing the safety, efficacy, and therapeutic mechanisms of Chinese medicines. It has also helped improve the credibility and popularity of Chinese medicine. Network pharmacology provides a new methodological perspective to identify and visualize the potential interaction network of TCM against multifactorial diseases. Under the “multicomponent, multitarget, multipathway model,” Chinese medicine has demonstrated satisfactory clinical efficacy in several complex diseases. However, novel ideas and methods are urgently needed to elucidate the complex interactions between TCM and diseases.

Recently, there has been a gradual increase in research on TCM for cancer treatment. Chinese medicine has the potential to treat digestive system tumors, alleviate the common complications associated with digestive system tumors, and reduce the adverse effects of Western medical treatments.^24,25 In mechanistic studies, TCM-based treatment has been shown to induce tumor cell apoptosis, inhibit tumor cell proliferation, and inhibit epithelial-mesenchymal transition.²⁶ Therefore, this study is the first to utilize network pharmacology and molecular docking, GO and KEGG pathway enrichment analysis, and systematic experimental validation to predict the core components, core targets, and possible mechanisms of action of QLD for CRC treatment. In this study, first, among all the active ingredients, the degree values for quercetin, kaempferol, diosgenin, nobiletin, cryptotanshinone, luteolin, and naringenin were found to be relatively high via Cytoscape 3.9.1 software, which indicates a high percentage of binding to intersecting targets. Therefore, we selected them as possible core active ingredients for QLD that might play a key role in treating CRC.

Quercetin has been shown to exert antitumor effects by modulating cell cycle progression, inhibiting cell proliferation, promoting apoptosis, inhibiting angiogenesis and metastatic progression, and thereby affecting autophagy.²⁷ Kaempferol, a plant-derived flavonoid, inhibits tumor growth and promotes apoptosis by modulating signaling pathways and exerting anticancer and antioxidant effects.²⁸ Diosgenin has been reported to have structural similarity to estrogen, and in a few in vitro and in vivo preclinical studies, it has shown proapoptotic and anticancer effects on various cancers.²⁹ Nobiletin enhances drug sensitivity, induces cancer cell death, and inhibits malignant tumor invasion and migration.³⁰ It significantly inhibits the growth of hepatic cancer cells.³¹ Cryptotanshinone exerts anticancer effects through various signaling pathways against various cancers, including those of the bowel, lung, breast, ovary, oral cavity, and bladder.³² Studies have shown that luteolin also plays a vital role in inhibiting cancer metastasis, inducing apoptosis and exerting anti-inflammatory effects.³³ Attention has also been given to the potential health benefits of luteolin, such as its anticancer, antimicrobial, anti-inflammatory, antioxidant, and antidiabetic effects, and their mechanisms.³⁴ Naringenin has also shown antiproliferative properties against a wide range of cancers, including lung, breast, and ovarian cancers.³⁵

A total of 194 drug targets for QLD and 1590 CRC disease targets were screened by intersecting the targets of drug components with those of CRC, which yielded 147 intersecting targets. On the basis of the results of the PPI network analysis and five algorithms in Cytoscape 3.9.1 software, AKT1, IL6, CASP3, EGFR, TP53, and TNF were identified as core targets for the treatment of CRC.

The AKT1 gene is most commonly mutated in cancer patients, and the aberrant activation of this pathway is associated with cell transformation, tumorigenesis, cancer progression, and drug resistance.³⁶ IL6 plays multiple roles in regulating immunity, metabolism, aging, and cancer.³⁷ CASP3 is a convergence point for signaling in response to multiple apoptotic stimuli, and its activation is a potential marker of the irreversible stage of apoptosis.³⁸ EGFR is a driver of tumorigenesis, and its signaling activates a variety of biological processes in mammalian cells, including cell proliferation, migration, differentiation, and apoptosis.³⁹ The TP53 gene, considered the most important oncogene, plays a major role in cancer formation, as it is involved in DNA repair, senescence, cell cycle control, autophagy, and apoptosis.⁴⁰ TNF, a proinflammatory cytokine, coordinates tissue homeostasis by controlling cytokine production, cell survival, and cell death.⁴¹

KEGG pathway enrichment analysis was carried out to identify pathways related to cancer, lipid and atherosclerosis, chemical carcinogenesis-receptor activation, the HIF-1 signaling pathway, the TNF signaling pathway, cellular senescence, EGFR tyrosine kinase inhibitor resistance, platinum drug resistance, and the FoxO signaling pathway. Afterward, the bioinformatics results were validated by experimental studies, such as the CCK-8 assay, colony formation assay, wound healing assay, and western blot. Furthermore, the antiproliferative and migratory effects of kaempferol on CRC were demonstrated in a dose-dependent manner. Kaempferol is a main ingredient of QLD; the proliferation and migration of colorectal cancer cells were inhibited after kaempferol treatment in this study, and the AKT/cyclin D1 pathway was inhibited. These results indicate that QLD can exert antitumor effects by regulating core molecules or pathways in CRC. We will continue to explore the values and mechanisms of QLD for the treatment of CRC in the future.

Conclusion

To the best of our knowledge, this study is the first to use a combination of network pharmacology, molecular docking, and basic research to explore the mechanism of action of QLD in the treatment of CRC, which provides a biological basis for the clinical application of QLD in tumor therapy. Moreover, the oncogenic effect of QLD on CRC was validated via in vitro experiments. We predicted 6 core targets and investigated whether kaempferol could inhibit the proliferation of colorectal cancer cells through the AKT/cyclin D1 signaling pathway. There are two possible limitations in this study. First, the experiments only verified that the proliferation of colorectal cancer cells was inhibited. Animal model experiments were not performed because of the long study period and high cost. The second limitation is that the effects of the different contents of the components on the potential targets and mechanism of action were ignored. In brief, the alternative mechanism of action of QLD in the inhibition of CRC should be thoroughly investigated, and the specific mechanism of action of QLD and its value in combined tumor therapy still has a long way to go.

Supplemental Material

sj-docx-1-npx-10.1177_1934578X241306229 - Supplemental material for Network Pharmacology, Molecular Docking, and Experimental Validation to Investigate the Mechanism of Qifu Longkui Decoction in the Treatment of Colorectal Cancer

Supplemental material, sj-docx-1-npx-10.1177_1934578X241306229 for Network Pharmacology, Molecular Docking, and Experimental Validation to Investigate the Mechanism of Qifu Longkui Decoction in the Treatment of Colorectal Cancer by Yaling Xiong, Yihao Liu, Xia Chen, Shuiwen Tang and Zhiyuan Jian in Natural Product Communications

Footnotes

Abbreviations

Acknowledgements

The authors would like to thank Guangxi Key Laboratory of Tumor Immunology and Microenvironmental Regulation for providing the necessary facilities and resources for this research. We thank Yuchuan TCM for sharing his data mining experience.

Author Contributions

Yaling Xiong: Writing - original draft, Conceptualization, Investigation, Methodology, Visualization, Data curation. Yihao Liu: Writing - original draft, Visualization, Software, Formal analysis, Conceptualization. Xia Chen: Investigation, Resources. Shuiwen Tang: Investigation, Formal analysis. Zhiyuan Jian: Writing - review & editing, Supervision, Project administration, Conceptualization, Funding acquisition, Data curation.

Data Availability

All data during this study are included in this article and its supplementary information files.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical Approval

Ethical Approval is not applicable for this article.

Funding

This research was supported by the Guangxi Medical and Health Key (Cultivation) Discipline Construction Project. This research was supported by Guilin Scientific Research and Technology Development Program Project (20210227-7-8).

ORCID iD

Zhiyuan Jian

Statement of Human and Animal Rights

This article does not contain any studies with human or animal subjects.

Statement of Informed Consent

There are no human subjects in this article and informed consent is not applicable.

Supplemental Material

Supplemental material for this article is available online.

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