scholarly journals Systematic Elucidation of the Potential Mechanisms of Core Chinese Materia Medicas in Treating Liver Cancer Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Zhulin Wu ◽  
Lina Yang ◽  
Li He ◽  
Lianan Wang ◽  
Lisheng Peng
Keyword(s):  
Data Mining ◽  
Liver Cancer ◽  
Signaling Pathways ◽  
Target Genes ◽  
Primary Liver Cancer ◽  
Network Pharmacology ◽  
Data Mining Technique ◽  
Antitumor Effects ◽  
Bioactive Ingredients ◽  
Common Target

Objective. In this study, the data mining method was used to screen the core Chinese materia medicas (CCMMs) against primary liver cancer (PLC), and the potential mechanisms of CCMMs in treating PLC were analyzed based on network pharmacology. Methods. Traditional Chinese medicine (TCM) prescriptions for treating PLC were obtained from a famous TCM doctor in Shenzhen, China. According to the data mining technique, the TCM Inheritance Support System (TCMISS) was applied to excavate the CCMMs in the prescriptions. Then, bioactive ingredients and corresponding targets of CCMMs were collected using three different TCM online databases, and target genes of PLC were obtained from GeneCards and OMIM. Afterwards, common targets of CCMMs and PLC were screened. Furthermore, a network of CCMMs bioactive ingredients and common target gene was constructed by Cytoscape 3.7.1, and gene ontology (GO) and signaling pathways analyses were performed to explain the mechanism of CCMMs in treating PLC. Besides, protein-protein interaction (PPI) analysis was used to identify key target genes of CCMMs, and the prognostic value of key target genes was verified using survival analysis. Results. A total of 15 high-frequency Chinese materia medica combinations were found, and CCMMs (including Paeoniae Radix Alba, Radix Bupleuri, Macrocephalae Rhizoma, Coicis Semen, Poria, and Curcumae Radix) were identified by TCMISS. A total of 40 bioactive ingredients (e.g., quercetin, kaempferol, and naringenin) of CCMMs were obtained, and 202 common target genes of CCMMs and PLC were screened. GO analysis indicated that biological processes of CCMMs were mainly involved in response to drug, response to ethanol, etc. Pathway analysis demonstrated that CCMMs exerted its antitumor effects by acting on multiple signaling pathways, including PI3K-Akt, TNF, and MAPK pathways. Also, some key target genes of CCMMs were determined by PPI analysis, and four genes (MAPK3, VEGFA, EGF, and EGFR) were found to be correlated with survival in PLC patients. Conclusion. Based on data mining and network pharmacology methods, our results showed that the therapeutic effect of CCMMs on PLC may be realized by acting on multitargets and multipathways related to the occurrence and development of PLC.

scholarly journals Potential Molecular Target Prediction and Docking Verification of Hua-Feng-Dan in Stroke Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Ping Yang ◽  
Haifeng He ◽  
Shangfu Xu ◽  
Ping Liu ◽  
Xinyu Bai
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Target Genes ◽  
Target Prediction ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Core Network ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Highly Correlated

Objective. Hua-Feng-Dan (HFD) is a Chinese medicine for stroke. This study is to predict and verify potential molecular targets and pathways of HFD against stroke using network pharmacology. Methods. The TCMSP database and TCMID were used to search for the active ingredients of HFD, and GeneCards and DrugBank databases were used to search for stroke-related target genes to construct the “component-target-disease” by Cytoscape 3.7.1, which was further filtered by MCODE to build a core network. The STRING database was used to obtain interrelationships by topology and to construct a protein-protein interaction network. GO and KEGG were carried out through DAVID Bioinformatics. Autodock 4.2 was used for molecular docking. BaseSpace was used to correlate target genes with the GEO database. Results. Based on OB ≥ 30% and DL ≥ 0.18, 42 active ingredients were extracted from HFD, and 107 associated targets were obtained. PPI network and Cytoscape analysis identified 22 key targets. GO analysis suggested 51 cellular biological processes, and KEGG suggested that 60 pathways were related to the antistroke mechanism of HFD, with p53, PI3K-Akt, and apoptosis signaling pathways being most important for HFD effects. Molecular docking verified interactions between the core target (CASP8, CASP9, MDM2, CYCS, RELA, and CCND1) and the active ingredients (beta-sitosterol, luteolin, baicalein, and wogonin). The identified gene targets were highly correlated with the GEO biosets, and the stroke-protection effects of Xuesaitong in the database were verified by identified targets. Conclusion. HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could be valuable to evaluate the antistroke effects of traditional Chinese medicines.

scholarly journals A Network Pharmacology Approach to Explore the Mechanisms of Shugan Jianpi Formula in Liver Fibrosis

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Chang Fan ◽  
Fu Rong Wu ◽  
Jia Fu Zhang ◽  
Hui Jiang
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Liver Fibrosis ◽  
Signaling Pathways ◽  
Target Genes ◽  
Janus Kinase ◽  
Target Proteins ◽  
Effective Components ◽  
Search Tool ◽  
Common Target

Purpose. We explored the mechanism of Shugan Jianpi Formula (SGJPF) and its effective components for the treatment of liver fibrosis (LF). Materials and Methods. We collected the active ingredients in SGJPF through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and screened the effective components by absorption, distribution, metabolism, and excretion. Herb-associated target proteins were predicted and screened based on the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine and Search Tool for Interactions of Chemicals databases. LF-associated target proteins were predicted and screened based on the Online Mendelian Inheritance in Man® Database and Comparative Toxicogenomics Database. Common genes with LF and herbs were selected, and Cytoscape 3.5.1 software was used to construct an herb pathway and component-LF common target network. The Search Tool for the Retrieval of Interacting Genes/Proteins was used to build a protein-protein interaction, and quantitative PCR was used to verify the related target genes. Finally, clusterProfiler was applied for the analysis of Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. Results. The pharmacological network contained 252 active compounds (e.g., Astragaloside A, saikosaponin, linoleic acid, and Poria acid A), 84 common target genes, and 94 significant signaling pathways. Among them, interleukin 6 (IL-6), tumor protein 53 p53 (TP53), prostaglandin-endoperoxide synthase 2 (PTGS2), AKT1, IL-1β, and the nucleotide-binding and oligomerization domain-like receptor and Janus kinase-signal transducer and activator of transcription signaling pathways were selected as the critical target gene and critical signal pathway, respectively. Conclusion. The mechanisms of SGJPF in protecting against LF include the regulation of multiple targets such as IL-6, TP53, PTGS2, and AKT1. These target proteins affect LF through various signal transduction pathways.

scholarly journals Network Pharmacology‐Based Study on the Active Component and Mechanism of the Anti-Gastric-Cancer Effect of Herba Sarcandrae

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Li Han ◽  
Ying Han
Keyword(s):  
Gastric Cancer ◽  
Signaling Pathways ◽  
Signaling Pathway ◽  
Target Genes ◽  
Scientific Basis ◽  
Gene Expression Omnibus ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Pathway Network

Background. Herba Sarcandrae is used in the clinical practice of traditional Chinese medicine to deal with gastric cancer. However, there are few studies on its precise mechanism. Method. In this study, a network pharmacological approach was utilized to construct a molecular/target/pathway molecular regulatory network for the anti-gastric-cancer effect of Herba Sarcandrae. The active components of Herba Sarcandrae and their potential mechanisms were explored. Chemical components of the Herba Sarcandrae were identified through a database, and they were evaluated and screened based on oral bioavailability and drug similarity. Results. Genes related to gastric cancer were found in the Gene Expression Omnibus (GEO) database, and gene targets related to anti-gastric-cancer were chosen by comparison. Using annotation, visualization, and a comprehensive discovery database, the function and related pathways of target genes were analyzed and screened. Cytoscape software was utilized to construct a component/target/pathway network for the antitumor effect of Herba Sarcandrae. Finally, 6 drug ingredients and 29 target genes related to gastric cancer were detected. IL-17 signaling pathway, NF-kappa B signaling pathway, and other signaling pathways were significantly enriched. Many signaling pathways that directly act on tumors and indirect pathways inhibit the development of gastric cancer. Conclusion. This study provides a scientific basis for further elucidating the mechanism of the anti-gastric-cancer effect of Herba Sarcandrae.

scholarly journals Deciphering the Key Pharmacological Pathways and Targets of Yisui Qinghuang Powder That Acts on Myelodysplastic Syndromes Using a Network Pharmacology-Based Strategy

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Zijian Han ◽  
Luping Song ◽  
Kele Qi ◽  
Yang Ding ◽  
Mingjun Wei ◽  
...  
Keyword(s):  
Myelodysplastic Syndromes ◽  
Target Genes ◽  
Network Pharmacology ◽  
Analysis Tool ◽  
Antitumor Effects ◽  
Active Compounds ◽  
Pharmacological Mechanism ◽  
Putative Target ◽  
Target Disease ◽  
Qinghuang Powder

Background. Yisui Qinghuang powder (YSQHP) is an effective traditional Chinese medicinal formulation used for the treatment of myelodysplastic syndromes (MDS). However, its pharmacological mechanism of action is unclear. Materials and Methods. In this study, the active compounds of YSQHP were screened using the traditional Chinese medicine systems pharmacology (TCMSP) and HerDing databases, and the putative target genes of YSQHP were predicted using the STITCH and DrugBank databases. Then, we further screened the correlative biotargets of YSQHP and MDS. Finally, the compound-target-disease (C-T-D) network was conducted using Cytoscape, while GO and KEGG analyses were conducted using R software. Furthermore, DDI-CPI, a web molecular docking analysis tool, was used to verify potential targets and pathways. Finally, binding site analysis was performed to identify core targets using MOE software. Results. Our results identified 19 active compounds and 273 putative target genes of YSQHP. The findings of the C-T-D network revealed that Rb1, CASP3, BCL2, and MAPK3 showed the most number of interactions, whereas indirubin, tryptanthrin, G-Rg1, G-Rb1, and G-Rh2 showed the most number of potential targets. The GO analysis showed that 17 proteins were related with STPK activity, PUP ligase binding, and kinase regulator activity. The KEGG analysis showed that PI3K/AKT, apoptosis, and the p53 pathways were the main pathways involved. DDI-CPI identified the top 25 proteins related with PI3K/AKT, apoptosis, and the p53 pathways. CASP8, GSK3B, PRKCA, and VEGFR2 were identified as the correlative biotargets of DDI-CPI and PPI, and their binding sites were found to be indirubin, G-Rh2, and G-Rf. Conclusion. Taken together, our results revealed that YSQHP likely exerts its antitumor effects by binding to CASP8, GSK3B, PRKCA, and VEGFR2 and by regulating the apoptosis, p53, and PI3K/AKT pathways.

Exploration of the Potential Mechanism of Calculus Bovis in Treatment of Primary Liver Cancer by Network Pharmacology

2020 ◽  
Vol 23 ◽  
Author(s):  
Zhen Zhang ◽  
Puhua Zeng ◽  
Wenhui Gao ◽  
Ruoxia Wu ◽  
Tianhao Deng ◽  
...  
Keyword(s):  
Liver Cancer ◽  
Small Molecules ◽  
Caspase 3 ◽  
Primary Liver Cancer ◽  
Network Pharmacology ◽  
Potential Mechanism ◽  
Vitro Experiment ◽  
In Vitro Experiment ◽  
Long Time

Aim and Objective: Calculus Bovis (CB) has been employed to treat diseases for a long time. It has been identified to play significant anti-inflammatory and anti-tumor roles. However, the mechanism of treating primary liver cancer (PLC) remains to be revealed. This study aims to clarify the molecules and mechanisms of CB in treating PLC. Materials and Methods: After oral bioavailability (OB) and drug-likeness (DL) screening, 15 small molecules were identified as the potential ingredients against PLC. Following this, related targets network constructions and pathways were applied to clarify the mechanism of CB in treating PLC. An in vitro experiment was carried out to identify the function of CB in treating PLC. Results: Eleven compounds of CB were identified that play an anti-PLC role, including oleanolic acid, ergosterol, ursolic acid, etc. The potential targets which were observed include: IL6, MAPK-8, VEGFA, Caspase-3, etc. Further analysis showed that the mechanism of CB in the treatment of PLC involved apoptosis-related pathways and immune- related pathways. Conclusion: In summary, the current study combines network pharmacology and in vitro experiments to reveal the mechanism of CB against PLC. We concluded that 11 ingredients of CB have an anti-PLC effect. Furthermore, CB plays a key role in treating PLC mainly by apoptosis-related pathways and immune-related pathways. Our experiment verifies that CB promotes the apoptosis of SMMC-7721.

Discovery of Biomarkers in Hepatocellular Carcinoma Metastasis Using Bioinformatic Analysis

2020 ◽  
Vol 15 ◽  
Author(s):  
Jinrui Wei ◽  
Haroon ur Rashid ◽  
Lichuan Wu
Keyword(s):  
Data Mining ◽  
Liver Cancer ◽  
Mirna Target ◽  
Cancer Metastasis ◽  
Target Genes ◽  
Interaction Analysis ◽  
Gene Interaction ◽  
Bioinformatic Analysis ◽  
Mirna Microarray ◽  
Carcinoma Metastasis

Background: Liver cancer is one of the most deadly malignancies worldwide. Tumor metastasis is the main cause of liver cancer related death. So far the mechanism of liver cancer metastasis are far away from fully elucidated. In this study, we aim to discover key regulators involved in liver cancer metastasis by data mining. Methods: Two different types of data including mRNA microarray (GSE6222 and GSE6764) and miRNA microarray (GSE67138) were analyzed. A total of 83 intersectant differently expressed genes (DEGs) with same expression pattern in GSE6222 and GSE6764 were identified. One hundred and thirty one differently expressed miRNAs (DEMs) were identified in GSE 67138. Further, a total of 26 pairs of miRNAtarget including 18 DEMs and 13 DEGs were identified as critical miRNA-target axis via miRNA-target gene interaction analysis. Result and Conclusion: Among the 18 DEMs and 13 DEGs, 10 miRNAs and 10 target genes are significantly correlated with patients’ survival (p < 0.05). Our results and methods might be interesting for data mining and helpful for further experimental functional validation.

Analysis of Herbal Mechanisms and Prescriptions for Chronic Cerebral Circulatory Insufficiency Based on Data Mining and Network Pharmacology

2021 ◽  
Vol 24 ◽  
Author(s):  
Ying Yu ◽  
Gong Zhang ◽  
Tao Han ◽  
Hai-liang Huang
Keyword(s):  
Signaling Pathways ◽  
Target Genes ◽  
Herbal Medicines ◽  
Circulatory System ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Hormone Regulation ◽  
Active Ingredients ◽  
The Core ◽  
Circulatory Insufficiency

Background: Traditional Chinese medicine has accumulated rich resources and experience through clinical research to explore the prevention and treatment of chronic cerebral circulatory insufficiency, but current medicine lacks in-depth research and confirmation on the established protocols and mechanism of prescribed TCMs at the macro and micro levels. Objective: To explore the prescription of Chinese medicines for the treatment of chronic cerebral circulation insufficiency (CCCI) and to explore the mechanism of core drugs. Methods: 229 Chinese prescriptions for CCCI were collected from CNKI, CBM, VIP and WANFANG databases. Analyze the frequency and association rules of drugs and to extract the core drugs by TCMISSV2.5 software. The active ingredients and targets were obtained by TCMSP, and genes of CCCI were collected from the DisGeNET, OMIM, DrugBank disease databases. The intersection targets of herbal medicine and disease was imported into the STRING database for PPI network. The key targets were screened by network topology algorithm. The Systems Dock website was used to verify the molecular docking. The GOEAST and DAVID tools were used to perform GO and KEGG pathway analysis with the key target genes. Results: 117 drugs involved in 229 prescriptions were identified, 2 core drugs were identified. We identified 8 active ingredients, which were mandenol, myricanone, perlolyrine, senkyunone, wallichilide, sitosterol, beta-sitosterol and stigmasterol. 371 herbal targets predicted and 335 disease targets. The enrichment analysis showed that the core herbal medicines could prevent CCCI by 15 key signaling pathways. Conclusion: There are direct or indirect connections in key signaling pathways, which not only participate in energy metabolism, hormone regulation, signal transduction, but also play a role in the comprehensive intervention of nervous system, immune system, circulatory system and other systems, which is consistent with the comprehensive pathogenesis of CCCI induced by multiple factors.

scholarly journals Clinical Evidence-Guided Anti-rheumatoid Arthritis Study of Shuji Tablet in Adjuvant-Induced Arthritis Rats and Mechanism Exploration via Network Pharmacological Approach

2021 ◽  
Vol 12 ◽  
Author(s):  
Weibo Dai ◽  
Jing Yang ◽  
Haili Cao ◽  
Zhuqiang Wang ◽  
Guangru Li ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Signaling Pathways ◽  
Target Genes ◽  
Histopathological Examination ◽  
Cartilage Damage ◽  
Leg Pain ◽  
Network Pharmacology ◽  
Adjuvant Induced Arthritis ◽  
Pharmacological Approach ◽  
Systemic Symptoms

Background: Rheumatoid arthritis (RA) is a kind of chronic autoimmune disease with several tissues damaged. Shuji tablet (SJT) is a prescription approved for treating lumbago and leg pain in the clinic. However, the efficacy of SJT against RA is still unknown. This study aims to evaluate the therapeutic effect of SJT on adjuvant-induced arthritis (AIA) rats and explore the mechanism via a network pharmacological approach.Methods: AIA rats were treated with SJT for 30 days at the dosages of 3.6, 1.8, and 0.9 g/kg, respectively, and the anti-RA effect was determined by measuring paw swelling, systemic symptoms score, arthritis index, and histopathological change. ELISA assay was used to evaluate the level of inflammatory cytokines in serum. The mechanism exploration and target prediction of SJT against RA were performed via a network pharmacological approach.Results: SJT showed excellent alleviation on AIA rats, with evidence of reducing paws swelling, decreasing systemic symptoms score, and arthritis index. Furthermore, SJT significantly reduced the serum cytokines of IL-6, IL-1β, TNF-α in AIA rats. Histopathological examination showed SJT remarkably reduced synovial hyperplasia, cartilage damage, and inflammatory infiltration in the secondary-side paws. According to network pharmacological analysis, 208 candidate compounds and 445 potential targets of SJT were identified, and 4465 RA therapy-related targets were searched out. Subsequently, 292 target genes of SJT were speculated to be associated with RA treatment, among which the top 5 “response values” targets were STAT3, AKT1, JUN, HSP90AA1, TNF. GO and KEGG enrichment analysis suggested that 45 signaling pathways were associating with SJT treating RA. The top 10 signaling pathways were PI3K-Akt, MAPK, AGE-RAGE pathway in diabetic complications, Ras, HIF-1, TNF, Chemokine, IL-17, FoxO, and Rap1.Conclusion: Our experimental study showed that SJT significantly alleviated rheumatoid arthritis of AIA rats. Network pharmacology showed that the key targets of SJT against RA probably were STAT3, AKT1, JUN, HSP90AA1, TNF, and the potential mechanism was associated with modulation on the signaling pathways of PI3K-Akt, MAPK, Ras, AGE-RAGE, HIF-1, TNF, chemokine, IL-17, FoxO, Rap 1. Our study strongly provides evidence for Shuji tablet in RA therapy and would enlarge its application in the clinic.

scholarly journals Activated TAZ Induces Liver Cancer in Collaboration with EGFR/HER2 Signaling Pathways

2021 ◽  
Author(s):  
Hyuk Moon ◽  
Hye Jin Choi ◽  
Do Young Kim ◽  
Simon Weonsang Ro
Keyword(s):  
Liver Cancer ◽  
Signaling Pathways ◽  
Primary Liver Cancer ◽  
Active Form ◽  
Health Concern ◽  
Liver Carcinogenesis ◽  
Regulator Protein ◽  
Incidence And Mortality ◽  
Her2 Signaling ◽  
Immunohistochemical Analyses

Abstract Liver cancer is a major global health concern due to the steady increases in its incidence and mortality. Transcription factors, yes-associated protein (YAP) and WW domain-containing transcription regulator protein 1 (WWTR1, also known as TAZ)have emerged as critical regulators in human hepatocellular carcinoma (HCC) and cholangiocarcinoma (CC), the two major types of primary liver cancer. However, our study as well as other previous reports have shown that activation of YAP and TAZ (YAP/TAZ) in adult murine livers is insufficient for the development of liver cancer, suggesting a requirement for an additional oncogenic collaborator for liver carcinogenesis in adulthood. Therefore,we sought to identifythe oncogenic partners of YAP/TAZ that promote hepatocarcinogenesis in adults. Through database analyses, we identified EGFR/HER2signaling to be essential in human cancerswith high TAZ activity.Furthermore,immunohistochemical analyses showedthat human HCC and CC tissues with high YAP/TAZ activities exhibited concomitant activation of EGFR/HER2downstream signaling pathways. To demonstrate that EGFR/HER2 signaling promotes YAP/TAZ-mediated hepatocarcinogenesis, a constitutively active form of TAZ was simultaneously expressed in murine adult livers with effector molecules downstream of EGFR/HER2 signaling pathways.Interestingly, activated TAZ and BRAFinduced HCC, whereas activated TAZ and PI3K led to the development of CC-like cancer, demonstrating that TAZ collaborates with EGFR/HER2 signaling pathways to induce both HCC and CC.

Exploration of  the mechanism of Ziyin Tongluo Formula on preventing and treating postmenopausal osteoporosis based on the network pharmacology

2020 ◽  
Author(s):  
Rong-Bin Chen ◽  
Ying-Dong Yang ◽  
Kai Sun ◽  
Shan Liu ◽  
Wei Guo ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Postmenopausal Osteoporosis ◽  
Target Genes ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Regulation Of Transcription ◽  
Active Ingredients ◽  
Active Components ◽  
Kegg Pathways ◽  
Key Genes

Abstract Background Postmenopausal osteoporosis (PMOP) is a global chronic and metabolic bone disease that poses huge challenges to individuals and society. Previous studies have confirmed that Ziyin Tongluo Formula (ZYTLF) has a good clinical effect in the treatment of PMOP. However, the material basis and mechanism of ZYLTF against PMOP has not been thoroughly explained. Methods TCMSP, TCMID, and BATMAN-TCM databases were used to identify the active ingredients and their putative targets. Genes associated with PMOP were mined from GeneCards, OMIM, DisGeNET databases, and then mapped with the putative targets to obtain overlapping target genes. A network model of "herb-active ingredient-overlapping target genes" was constructed and a protein-protein interaction network of overlapping target genes was built and the key genes were selected based on the MCC algorithm. The key genes were imported to the DAVID database to performs GO and KEGG pathway enrichment analyses. Results Ninety-two active components of ZYTLF corresponded to 243 targets, with 129 target genes interacting with PMOP, and 50 key genes were selected. GO analysis results showed that biological process mainly included positive regulation of transcription, negative regulation of apoptosis, and cell components were mainly nucleus, cytoplasm, and molecular functions mainly included enzyme binding, protein binding and transcription factor binding. There were two main types of significant KEGG pathways in PMOP, hormone-related signaling pathways (estrogen, prolactin, thyroid hormone) and inflammation-related pathways (TNF, PI3K-Akt, MAPK ). Conclusions The underlying therapeutic mechanisms of ZYTLF action on PMOP maybe is that, the active ingredients such as quercetin, kaempferol, luteolin act on ESR1, TNF, IL6, MAPK8 and other key genes, which mainly enrich in estrogen, TNF, PI3K-Akt, MAPK and other signaling pathways.

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