Investigate the Effects of Qingre Zaoshi Jiedu Recipe on Cervical Inflammatory–Cancer Transformation Associated with High-Risk Human Papillomavirus Using Network Pharmacology, Gene Expression Omnibus, and Molecular Docking Methods

Abstract

Objective

To investigate the active components and mechanisms by which Qingre Zaoshi Jiedu Recipe influences the transformation from cervical high-risk human papillomavirus (HR-HPV)-related cervicitis to cancer, utilizing network pharmacology, Gene Expression Omnibus (GEO) data, and molecular docking techniques.

Methods

Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), HERB, and the Encyclopedia of Traditional Chinese Medicine (ETCM) databases were used to screen out the active ingredients and related targets of Qingre Zaoshi Jiedu Recipe. The GeneCards database for disease targets at different stages of HR-HPV-related cervicitis–cancer were searched. The String platform to construct a protein-protein interaction network and identify key targets was utilized. Enrichment analysis of intersecting genes was performed using the DAVID database. The GSE149763 dataset from the GEO to identify differential genes involved in the transformation from cervicitis to cervical cancer by comparing cervicitis with cervical intraepithelial neoplasia III and cervical cancer was utilized. R language to generate volcano plots, heat maps, and key target expression trend charts were employed. Molecular docking of key pathway targets and main compounds of Qingre Zaoshi Jiedu Recipe for HR-HPV-related cervicitis–cancer was performed using AutoDock Vina.

Results

The study identified 185 main active ingredients of Qingre Zaoshi Jiedu Recipe. The protein–protein interaction network indicates that the core targets for interfering with HR-HPV-related inflammation–cancer transformation include TNF, IL-6, IL-1β, CXCL8, IL-1α, IFN-γ, IL-10, CCL2, CCL5, and CXCL10. KEGG pathway analysis indicates that Qingre Zaoshi Jiedu Recipe primarily affects HR-HPV-related inflammation–cancer transformation via the Toll-like receptor signaling pathway. GEO analysis identified the Toll-like receptor pathway as crucial across various stages of cervicitis–cancer lesions, with CXCL10 emerging as a key target. Molecular docking analysis revealed that the primary components of Qingre Zaoshi Jiedu Recipe effectively bind to TLR4.

Conclusion

Qingre Zaoshi Jiedu Recipe can interfere with HR-HPV-related cervicitis–cancer transformation by acting on TLR4 through the Toll-like receptor pathway.

 

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Keywords

Qingre Zaoshi Jiedu Recipe - inflammatory-cancer transformation - HR-HPV - CXCL10 - TLR4 - Toll-like receptor signaling pathway

Introduction

Cervical cancer poses a significant threat to women's reproductive health. Despite a decline in incidence rates due to the widespread implementation of cervical cancer screening and human papillomavirus (HPV) vaccination programs, a substantial number of new cases and deaths continue to occur globally each year.[1] Research indicates a strong association between cervical cancer and infection with high-risk human papillomavirus (HR-HPV).[2] HR-HPV infection can cause a chronic inflammatory response in the cervix. Persistent chronic cervical inflammation creates a microenvironment that fosters cervical cancer development by encouraging cell proliferation, inhibiting apoptosis, and promoting angiogenesis. Inflammatory cells cause continuous stimulation and damage of cervical cells by secreting growth factors, cytokines and chemical factors. These factors influence cervical cancer cell behavior,[3] contributing to the formation of precancerous lesions and cancer progression. The progression from chronic inflammation to cancer is pivotal in the development of cervical cancer.[4] Understanding the mechanism behind the transformation from cervical inflammation to cancer and implementing proactive drug interventions are crucial for preventing and treating cervical cancer.[5] Clinical observations indicate that the traditional Chinese medicine (TCM) can eliminate persistent HR-HPV infections, reverses cervical lesion pathology, and delays cervical cancer progression,[6] while the precise targets and mechanisms underlying its action have not yet been fully elucidated. Hence, investigating the mechanisms by which TCM impedes the “inflammatory-cancerous” transformation in HR-HPV cervical cancer holds substantial clinical significance.

Qingre Zaoshi Jiedu Recipe represents an empirically derived prescription for the prevention and treatment of cervical diseases associated with HR-HPV infection. Our previous clinical investigations have demonstrated that this regimen effectively alleviates HR-HPV-related cervicitis and reverses low-grade squamous intraepithelial lesions (LSIL), thereby delaying the progression to cervical cancer. Additionally, it has been shown to reduce the expression levels of TLR4, CXCL10, and IL-6 in the cervical vaginal fluid of affected patients. Nevertheless, the precise mechanisms by which this regimen exerts its preventive and therapeutic effects on the “inflammation–cancer” transformation associated with HR-HPV-related cervical conditions remain to be elucidated. This study integrates network pharmacology, GEO data, and molecular docking techniques to investigate the potential effects of Qingre Zaoshi Jiedu Recipe on the transformation from cervical HR-HPV-related cervicitis to cancer, offering insights for its further development and application.

 

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Methods

Screening of Active Ingredients and Target Proteins of Qingre Zaoshi Jiedu Recipe

This study created a database of Qingre Zaoshi Jiedu Recipe's six-flavored herbs by searching Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), HERB, and the Encyclopedia of Traditional Chinese Medicine (ETCM) databases. Active ingredients were identified based on oral bioavailability (OB) of 30% or higher and drug-likeness (DL) of at least 0.18. The TCMSP database was used to find target proteins for these ingredients, which were then standardized using Uniprot. Duplicate genes were removed and constructed compound-target sites with Cytoscape 3.7.2 software. The network and perform topological analysis was visualized.

 

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Prediction of Targets for the High-Risk Human Papillomavirus-Related Inflammation–Cancer Transformation in the Treatment of Qingre Zaoshi Jiedu Recipe and Construction of Protein–Protein Interaction Network

Use GeneCards database to identify disease-related targets and eliminate duplicates. Search for genes linked to Qingre Zaoshi Jiedu Recipe's herb target proteins and HR-HPV targets. Upload the target proteins for active ingredients of Qingre Zaoshi Jiedu Recipe and HR-HPV targets to the bioinfogp platform (https://bioinfogp.cnb.csic.es/tools/venny/index.html). Select “Venn diagram” and find the intersection point between the active ingredient target of Qingre Jiedu Recipe and the HR-HPV target. Import the results into the STRING database, apply a high confidence filter (0.9), exclude isolated targets, restrict species to humans, determine interaction relationships, construct a protein–protein interaction (PPI) network, and generate a PPI network TSV file. Input the file into the software R 4.3.1, and screen the core target proteins with count > 3 times the average value.

 

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Enrichment Analysis

The DAVID (https://david.ncifcrf.gov/) offers extensive and systematic functional annotation for large-scale gene or protein lists, identifying the most significantly enriched biological information. Upload the intersection targets to the DAVID database. Choose “OFFICIAL GENE SYMBOL” for data type, “gene list” for table type, and “Homo sapiens” for both species and background. Then, use the “Functional Annotation Tool” to conduct GO and KEGG enrichment analyses. When screening, the limiting conditions are p < 0.05, FDR < 0.05. Examine the key biological pathways influenced by Qingre Zaoshi Jiedu Recipe's active ingredients in treating HR-HPV and explore the potential mechanisms involved.

 

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Pathway–Target Network Construction

Obtain targets and pathways through the top 20 KEGG pathways in 2.4, remove duplicates from the obtained targets, construct a pathway–target network with the obtained pathways, and input Cytoscape 3.9.1 for network Visual analysis to screen potential core targets with degree > 2.5 times the average value.

 

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Verification of the Mechanism of Cervical Inflammation–Cancer Transformation Based on the Gene Expression Omnibus (GEO) Database

The GEO database was utilized to identify terms such as HR-HPV, high risk human papillomavirus, cervicitis, cervical intraepithelial neoplasia (CIN), and LSIL. High-grade squamous intraepithelial lesion (HSIL), cervical cancer, and similar conditions as keywords to obtain the chip dataset of GSE149763. This dataset contains nine samples, three cases of cervicitis, three cases of CIN III, and three cases of cervical cancer in stage IIa. Use R software 4.2.2 to process the data, use | logFC | > 0.5, p < 0.05 as the filtering conditions to obtain differential genes, and select the differential genes of cervicitis versus CINIII, cervicitis versus cervical cancer as the markers of cervicitis–cancer transformation. For differential genes, use R language to draw volcano plots, heat maps, and key target expression trend charts.

 

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Molecular Docking

This study conducted molecular docking to verify the credibility of key targets and compounds involved in the transformation from cervicitis to cancer. Access the PDB database (http://www.rcsb.org/pdb) to obtain the crystal structure of the target and retrieve the 2D structure of the compound from the PubChem database (https://pubchem.ncbi.nlm.nih.gov/). Utilize the CB-Dock online tool (http://clab.labshare.cn/cb-dock/) for molecular docking, employing the docking score (affinity) to evaluate the interaction credibility between the target and the compound. A score of < − 7.0 kcal·mol⁻¹ signifies enhanced binding activity between the two groups. Use Ligplot software (Version 2.2) to display the docking combination with the best Affinity value. The software can automatically calculate interactions such as hydrogen bonds, hydrophobic interactions, or result comparisons formed between the receptor and the ligand.

 

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Results

Screening of Active Ingredients of Qingre Zaoshi Jiedu Recipe

A search of the TCMSP, HERB, ETCM database, applying the criteria of OB ≥ 30% and DL ≥ 0.18, identified 185 active ingredients, 411 targets in Qingre Zaoshi Jiedu Recipe, predominantly β-sitosterol, formononetin, kaempferol, quercetin, poriferast-5-en-3β-ol, inermine, odoratin, 2-[(3R)-8,8-dimethyl-3,4-dihydro-2H-pyrano[6,5-f]chromen-3-yl]-5-methoxyphenol and other ingredients ([Fig. 1]). Constructed compound-target sites with Cytoscape 3.7.2 software and visualized it ([Fig. 2]).

Fig. 1 Venn diagram of active ingredients between different databases.

Fig. 2 Active component of Qingre Zaoshi Jiedu Recipe–target network.

 

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Drug–Target–Disease Network

In the GeneCards database, there are 3421 HR-HPV-related targets, 11,563 cervical cervicitis-related targets, 1,716 cervical LSIL-related targets, 1,720 cervical HSIL related targets, and 3,449 cervical cancer-related intersection targets. Use Venn diagram to obtain the relationship between disease targets and drug targets at each stage in the course of HR-HPV-related cervicitis–cancer transformation intersection ([Fig. 3]). At each stage of inflammation–cancer transformation, drugs and diseases have common targets. There are 186 intersections between the targets related to Qingre Zaoshi Jiedu Recipe and those related to HR-HPV combined with cervical inflammation stage, 147 intersections with those related to HR-HPV combined with LSIL stage, 147 intersections with those related to HR-HPV combined with HSIL stage, and 157 intersections with those related to HR-HPV combined with cervical cancer stage. Among them, the HR-HPV-related LSIL group and the HR-HPV-related HSIL have the same number targets.

Fig. 3 Intersection target Venn diagram. (A) Venn diagram of the intersection of targets related to Qingre Zaoshi Jiedu Recipe and HR-HPV combined with cervicitis. (B) Venn diagram of the intersection of targets related to Qingre Zaoshi Jiedu Recipe and HR-HPV combined with cervical LSIL. (C) Venn diagram of the intersection of targets related to Qingre Zaoshi Jiedu Recipe and HR-HPV combined with cervical HSIL. (D) Venn diagram of the intersection of targets related to Qingre Zaoshi Jiedu Recipe and HR-HPV combined with cervical cancer. HSIL, high-grade squamous intraepithelial lesion; HR-HPV, high-risk human papillomavirus; LSIL, low-grade squamous intraepithelial lesion.

 

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Construction of the Protein–Protein Interaction Network and Identification of Key Targets

The PPI network diagrams generated via the String platform ([Fig. 4]). The PPI network involving the HR-HPV-related cervicitis consists of 186 nodes and 817 edges, with an average node degree of 8.78. The PPI network involving the HR-HPV-related LSIL consists of 147 nodes and 682 edges, resulting in an average node degree of 9.28. The PPI network involving cervical cancer associated with HR-HPV consists of 157 nodes and 704 edges, resulting in an average node degree of 8.97. The HR-HPV-related LSIL network is the same as the HR-HPV-related HSIL network. The top 10 targets ranked by node degree included TNF, IL-6, IL-1β, CXCL8, L1A, IFN-γ, IL-10, CCL2, CCL5, CXCL10, shown in [Table 1] and [Fig. 5].

Table 1 Top 10 targets with node degrees

Disease stage	Key target
HR-HPV-related cervicitis	TNF, IL-6, IL-1β, CXCL8, IL-1α, IFN-γ, IL-10, CCL2, CCL5, CXCL10
HR-HPV-associated cervical LSIL	TNF, IL-6, IL-1β, CXCL8, IL-1α, IFN-γ, IL-10, CCL2, CCL5, CXCL10
HR-HPV-associated cervical HSIL	TNF, IL-6, IL-1β, CXCL8, IL-1α, IFN-γ, IL-10, CCL2, CCL5, CXCL10
HR-HPV-associated cervical cancer	TNF, IL-6, IL-1β, CXCL8, IL-1α, IFN-γ, IL-10, CCL2, CCL5, CXCL10

Abbreviation: HR-HPV, high-risk human papillomavirus; HSIL, high-grade squamous intraepithelial lesion; LSIL, low-grade squamous intraepithelial lesion.

Fig. 4 PPI network. (A) The PPI network involving HR-HPV-related cervicitis. (B) The PPI network involving HR-HPV-associated cervical LSIL. (C) The PPI network involving HR-HPV-associated cervical HSIL. (D) HR-HPV-associated cervical cancer. HSIL, high-grade squamous intraepithelial lesion; LSIL, low-grade squamous intraepithelial lesion; HR-HPV, high-risk human papillomavirus; PPI, protein–protein interaction.

 

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Analysis of GO and KEGG Pathway Enrichment

The targets in the GO analysis are common targets between the components of Qingre Zaoshi Jiedu Recipe and HR-HPV-related cervicitis–cancer transformation at different disease stages. Qingre Zaoshi Jiedu Recipe can act on this target to exert its potential active. Judging from the top 10 biological functions ranked by correlation in GO enrichment analysis, the biological functions in the four stages of inflammation–cancer transformation are basically the same ([Fig. 6]).

Fig. 5 Target map of the top 10 node degrees.

Fig. 6 GO enrichment analysis diagram. (A) HR-HPV-related cervicitis. (B) HR-HPV-associated cervical LSIL. (C) HR-HPV-associated cervical HSIL. (D) HR-HPV-associated cervical cancer. HSIL, high-grade squamous intraepithelial lesion; LSIL, low-grade squamous intraepithelial lesion; HR-HPV, high-risk human papillomavirus.

KEGG pathway enrichment analysis of the common targets between the components of Qingre Zaoshi Jiedu Recipe and HR-HPV-related cervicitis–cancer transformation at different disease stages was conducted using the DAVID database, with significance set at p < 0.05. HR-HPV combined with cervicitis resulted in 230 pathways, HR-HPV combined with LSIL yielded 223 pathways, HR-HPV combined with HSIL yielded 223 pathways, and HR-HPV combined with cervical cancer stages yielded 218 pathways. The KEGG pathway enrichment analysis reveals that the top 15 pathways are notably similar across the four stages of inflammation–cancer transformation, with several inflammatory pathways, including the Toll-like receptor signaling pathway, being common ([Fig. 7]).

Fig. 7 KEGG enrichment analysis. (A) HR-HPV-related cervicitis. (B) HR-HPV-associated cervical LSIL. (C) HR-HPV-associated cervical HSIL. (D) HR-HPV-associated cervical cancer. HSIL, high-grade squamous intraepithelial lesion; LSIL, low-grade squamous intraepithelial lesion; HR-HPV, high-risk human papillomavirus.

 

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Verification of the Mechanism of Cervical Inflammation–Cancer Transformation Based on the GEO Database

Using the GEO database, the GSE149763 chip dataset was analyzed to identify differential genes. Specifically, genes differentiating cervicitis from CINIII and cervical cancer were selected to study cervicitis–cancer transformation, as depicted in [Fig. 8]. R language was employed to generate a volcano plot and heat maps of top 100 upregulated and downregulated key targets, as illustrated in [Fig. 9]. The Toll-like receptor pathway was identified as crucial, with CXCL10 as the primary target exhibiting an upregulation trend, as shown in [Table 2] and [Fig. 10].

Fig. 8 The intersection of GSE149763 chip cervicitis versus CINIII (N3) and cervicitis versus cervical cancer (CC) differential genes.

Fig. 9 (A–B) GSE149763 gene chip cervicitis–cancer transformation mechanism differential gene volcano diagram and heatmap of the top 100 upregulated and downregulated genes. (A) Cervicitis versus CINIII. (B) Cervicitis versus cervical cancer.

Table 2 The KEGG pathway enrichment analysis outcomes for differential genes

ID	KEGG pathway	Genes
hsa04110	Cell cycle	CCNA2, CCNE2, DDX11, PLK1, BUB1B, CDC7, ESCO2, TRIP13, BUB1
hsa04814	Motor proteins	CENPE, KIF4A, KIF14, KIF23, KIF20A, KIF11, KIF15
hsa04512	ECM–receptor interaction	TNXB, ITGB5, SPP1, HMMR
hsa04914	Progesterone-mediated oocyte maturation	CCNA2, PLK1, BUB1, AURKA
hsa04620	Toll-like receptor signaling pathway	CXCL10, CXCL8, CTSK, SPP1
hsa04114	Oocyte meiosis	CCNE2, PLK1, BUB1, AURKA
hsa03440	Homologous recombination	XRCC2, BRCA1, TOPBP1

Fig. 10 Differential expression trend chart of CXCL10 in different lesion stages of cervicitis–CINIII–cervical cancer.

 

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Molecular Docking of the Main Active Ingredients of Qingre Zaoshi Jiedu Recipe with Toll-Like Receptor 4

Toll-like receptor 4 (TLR4) plays a crucial role in the development of chronic inflammation and is involved in the pathogenesis of inflammation-associated cancers.[7] In cases of persistent cervical HR-HPV infection, there is an upregulation of TLR4 protein expression.[8] Building upon our previous research, we hypothesize that the Qingre Zaoshi Jiedu Recipe may attenuate the TLR4/CXCL10 signaling pathway through its active constituents. This study focuses on TLR4 and the primary components of Qingre Zaoshi Jiedu Recipe for further verification.

The docking activity of the main active ingredients of Qingre Zaoshi Jiedu Recipe, berberine, indirubin, quercetin, β-sitosterol, and TLR4 was verified by molecular docking. The research showed that the active ingredients of Qingre Zaoshi Jiedu Recipe for treating HR-HPV can combine with TLR4. The binding energies of various compounds with TLR4 are as follows: quercetin (−7.5 kcal·mol⁻¹), berberine (−7.2 kcal·mol⁻¹), corkine (-6.2 kcal·mol⁻¹), β-sitosterol (−7.1 kcal·mol⁻¹), indirubin (−7.1 kcal·mol⁻¹), and fritillary glycoside A (−8.1 kcal·mol⁻¹), indicating active ingredients and TLR4 can effective binding interactions ([Table 3] and [Fig. 11]).

Table 3 Results of docking between the main active ingredients of Qingre Zaoshi Jiedu Recipe and TLR4

Compound	Key target	Binding energy/(kcal·mol−1)
Quercetin	TLR4	−7.5 kcal·mol−1
Berberine	TLR4	−7.2 kcal·mol−1
β-Sitosterol	TLR4	−7.5 kcal·mol−1
Indirubin	TLR4	−7.1 kcal·mol−1

Fig. 11 (A–D) Molecular docking.

 

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Discussion

Cervical cancer poses a significant threat to women's reproductive health. There is a strong association between infection with HR-HPV and the development of this malignancy. In recent years, the interplay between inflammation and tumorigenesis has emerged as a prominent focus in oncological research. HR-HPV is implicated in the pathogenesis of cervical cancer through the induction of chronic inflammation. Currently, contemporary medicine lacks specific pharmacological agents capable of completely eradicating HR-HPV infections. In cases of chronic inflammation resulting from persistent HR-HPV infection, Western medical interventions are primarily symptomatic and often insufficient to effectively interrupt the progression from inflammation to cancer. In contrast, TCM, with its emphasis on “preventative treatment,” has demonstrated distinct advantages in managing HR-HPV infections. TCM has been shown to reduce local inflammatory responses in the cervix, reverse cervical lesions, and delay the onset of cervical carcinogenesis.[9] However, the precise targets and mechanisms of action of TCM remain inadequately elucidated. Consequently, a comprehensive investigation into the mechanisms by which TCM impedes the “inflammation–cancer” transformation associated with HR-HPV in cervical cancer is of significant clinical importance. Such research could also offer novel insights and methodologies for the prevention and treatment of cervical cancer.

In TCM, HR-HPV infection is classified under the category of “Leucorrhea.” Its pathogenesis is primarily attributed to factors such as unclean sexual practices, excessive sexual activity, emotional distress, and dietary imbalances. These factors contribute to the invasion of damp-heat and toxic heat into the uterus, subsequently altering the vaginal environment, compromising the immune defense system, and leading to cervical lesions that may eventually progress to cervical cancer. Previous research by the applicant has identified a correlation between cervical HR-HPV infection and a damp-heat constitution.[10] Damp-heat acts as an initiating factor in the “inflammation–cancer” transformation process.[11] The application of TCM strategies aimed at clearing heat, drying dampness, and detoxifying during the HR-HPV infection-related cervical “inflammation–cancer” transformation holds promise for halting the progression of lesions at an early stage and reducing the incidence of cervical cancer.[12] [13] Research has indicated that TCM, which clears heat, dries dampness, and detoxifies, can eliminate HR-HPV infections, lower inflammatory factors in the body, and consequently reverse cervical lesions, thereby decreasing cervical cancer rates.[14] [15] However, the exact mechanism by which medicine with the function of Qingre Zaoshi Jiedu prevents and treats HR-HPV-related cervical “inflammation–cancer” transformation remains unknown. This study explored the effects of the Qingre Zaoshi Jiedu Recipe on cervical “inflammatory-cancer transformation” linked to HR-HPV using network pharmacology, G, and molecular docking techniques.

This study employed network pharmacology to identify the active components of Qingre Zaoshi Jiedu Recipe and their key targets in the HR-HPV-related inflammation–cancer transformation process. A total of 185 active ingredients were obtained, berberine, β-Ingredients such as sitosterol and quercetin have multiple targets. Quercetin, known as 3,5,7,3′,4'-pentahydroxyflavone, is a significant natural flavonoid. Quercetin and its derivatives can affect different stages of the virus life cycle.[16] Quercetin can downregulate the contents of TLR4, NF-κB, tumor necrosis factor α (TNF-α), and IFN-γ.[17] Quercetin has certain negative conversion and anti-inflammatory effects on CINI patients infected with HR-HPV.[18] Quercetin modulates TGF-β1 and Smad4 expression in SiHa cervical cancer cells, leading to reduced cell proliferation and metastasis.[19] β-Sitosterol enhances mRNA expression of IFN-β and its downstream genes, reduces E7 protein expression to combat viruses, and inhibits SiHa cell growth.[20] Berberine, a natural compound with potent pharmacological activity, significantly reduces TNF-α levels and inhibits apoptosis and cell cycle progression in human cervical cancer cells. Indirubin anti-inflammatory functions, reduce the level of IL-1β.[21] [22] [23] [24] TNF-α is new antitumor medicine for therapy cancers that have CDK. The PPI network identifies IL-6, TNF, IL-1β, CXCL8, IL-1α, IFN-γ, IL-10, CCL2, CCL5, and CXCL10 as the primary targets of Qingre Zaoshi Jiedu Recipe in modulating HR-HPV-related inflammation–cancer transformation. CXCL10 belongs to the CXC chemokine family. Antigen-presenting cells, such as dendritic cells and macrophages, as well as tumor cells, produce this proinflammatory factor.[25] CXCL10 contributes to inflammation, antiviral responses, and the tumor microenvironment by promoting the production of cytokines like TNF-α, which intensifies the inflammatory response.[26] Recent studies indicate that CXCL10 is crucial in cervical inflammation and cancer, with significant upregulation observed in the cervical tissue of HPV-infected patients, including those with CIN and cervical squamous cell carcinoma.[27] [28]

KEGG pathway analysis indicated that Qingre Zaoshi Jiedu Recipe primarily disrupts HR-HPV-related inflammation–cancer transformation via the toll-like receptor signaling pathway. TLR4 is a key mediator in the process of chronic inflammation.[29] With the persistent infection of HR-HPV, TLR4 protein expression increases, which can induce cell necroptosis.[30] [31] In addition, activation of TLR4 can promote NF-κB activation and mediate the production of precursors such as interleukin-1β and IL-18, as well as upregulate the inflammasome NLRP3. Molecular docking analysis revealed that the primary components of Qingre Zaoshi Jiedu Recipe effectively bind to TLR4.

GEO analysis identified the toll-like receptor pathway as crucial across various stages of cervicitis–cancer lesions, with CXCL10 emerging as a key target exhibiting an up-regulation trend. Molecular docking analysis revealed that the primary components of Qingre Zaoshi Jiedu Recipe effectively bind to TLR4. The active components of Qingre Zaoshi Jiedu Recipe may disrupt the transformation from HR-HPV-related cervicitis to cancer via the TLR4 pathway.

 

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Conclusion

As mentioned in the review, through GEO and network pharmacology analysis, this article shows that Qingre Zaoshi Jiedu Recipe can intervene in HR-HPV-related cervicitis–cancer transformation through multicomponents and Toll-like receptor pathway. We will conduct experimental studies to further verify this.

 

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Conflict of Interest

The authors declare no conflict of interest.

CRediT Authorship Contribution Statement

Shanyun Wang and Jian Huang: visualization, funding acquisition, data curation, project administration, writing—original draft, and writing—review and editing; Linhua Yang: writing—review and editing; Jianfeng Zeng: supervision, formal analysis, methodology, validation, and writing—review and editing.

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Publication History

Received: 12 January 2025

Accepted: 17 March 2025

Article published online:
27 June 2025