scholarly journals Systems Pharmacology-Based Research on the Mechanism of Tusizi-Sangjisheng Herb Pair in the Treatment of Threatened Abortion

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Ming Yang ◽  
Jianghe Luo ◽  
Yan Li ◽  
Limian Xu
Keyword(s):  
Molecular Mechanisms ◽  
Transforming Growth Factor ◽  
Chinese Herb ◽  
Enrichment Analysis ◽  
First Trimester ◽  
Chinese Herbs ◽  
Pathway Enrichment Analysis ◽  
Systems Pharmacology ◽  
Mitogen Activated Protein ◽  
Threatened Abortion

Threatened abortion (TA) is a common complication with high incidence in the first trimester of pregnancy, which will end in miscarriage if not treated properly. The Chinese herbs Cuscutae Semen (Tusizi in Chinese) and Herba Taxilli (Sangjisheng in Chinese) first recorded in the ancient classic medical book Shennong Bencao Jing are effective and widely used as an herb pair for the treatment of TA, while the active ingredients and the functional mechanism of Tusizi-Sangjisheng herb pair treating TA are still unknown. In order to exploit the relationship between those two herbs and TA, systems pharmacology analysis was carried out in this study. A total of 75 ingredients of Tusizi-Sangjisheng were collected from Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP). 12 bioactive compounds were screened, and 153 directly related targets were predicted by systematic models. Besides, Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were used to systematically explore the potential mechanisms of Tusizi-Sangjisheng treating TA. Meanwhile, Compound-Target (C-T), Target-Disease (T-D), and Target-Pathway (T-P) networks were constructed to further quest the underlying functional mechanisms of Tusizi-Sangjisheng. As a result, 31 targets and 3 key pathways were found to be directly related to TA that includes mitogen-activated protein kinases (MAPKs), phosphatidylinositol-3-kinase/protein kinase B (PI3K-Akt), and transforming growth factor-β (TGF-β) signaling pathways. The results in this study may provide some valuable clues about the molecular mechanisms of the efficient Chinese herb pair Tusizi-Sangjisheng in the treatment of TA.

scholarly journals A Systems Pharmacology Approach for Identifying the Multiple Mechanisms of Action for the Rougui-Fuzi Herb Pair in the Treatment of Cardiocerebral Vascular Diseases

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Chun Li ◽  
Xia Du ◽  
Yang Liu ◽  
Qi-Qi Liu ◽  
Wen Bing Zhi ◽  
...  
Keyword(s):  
Molecular Mechanisms ◽  
Chinese Herb ◽  
Vascular Diseases ◽  
Enrichment Analysis ◽  
Chinese Herbs ◽  
Pathway Enrichment Analysis ◽  
High Morbidity ◽  
Active Ingredients ◽  
Active Compounds ◽  
System Pharmacology

Cardiocerebral vascular diseases (CCVDs) are the main reasons for high morbidity and mortality all over the world, including atherosclerosis, hypertension, myocardial infarction, stroke, and so on. Chinese herbs pair of the Cinnamomum cassia Presl (Chinese name, rougui) and the Aconitum carmichaelii Debx (Chinese name, fuzi) can be effective in CCVDs, which is recorded in the ancient classic book Shennong Bencao Jing, Mingyibielu and Thousand Golden Prescriptions. However, the active ingredients and the molecular mechanisms of rougui-fuzi in treatment of CCVDs are still unclear. This study was designed to apply a system pharmacology approach to reveal the molecular mechanisms of the rougui-fuzi anti-CCVDs. The 163 candidate compounds were retrieved from Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP). And 84 potential active compounds and the corresponding 42 targets were obtained from systematic model. The underlying mechanisms of the therapeutic effect for rougui-fuzi were investigated with gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Then, component-target-disease (C-T-D) and target-pathway (T-P) networks were constructed to further dissect the core pathways, potential targets, and active compounds in treatment of CCVDs for rougui-fuzi. We also constituted protein-protein in interaction (PPI) network by the reflect target protein of the crucial pathways against CCVDs. As a result, 21 key compounds, 8 key targets, and 3 key pathways were obtained for rougui-fuzi. Afterwards, molecular docking was performed to validate the reliability of the interactions between some compounds and their corresponding targets. Finally, UPLC-Q-Exactive-MSE and GC-MS/MS were analyzed to detect the active ingredients of rougui-fuzi. Our results may provide a new approach to clarify the molecular mechanisms of Chinese herb pair in treatment with CCVDs at a systematic level.

scholarly journals Network Pharmacology-Based Investigation For Predicting Active Ingredients And Potential Targets Of Strychnos Nux-Vomica L. In Treating Multiple Myeloma

2020 ◽  
Author(s):  
Yan Zhou ◽  
Jianping Shen ◽  
Keting Jin ◽  
Chenjun Lin ◽  
Zirui Hong ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Molecular Mechanisms ◽  
Chinese Herb ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Topological Parameters ◽  
Pharmacological Potential ◽  
Underlying Mechanisms

Abstract Background: Strychnos nux-vomica L. (SN)，a classic Chinese herb, have long been used for the treatment of cancer for many years, However, the pharmacological mechanisms of SN in treatment of Multiple myeloma L.remain vague.The aim of this study was to examine the network pharmacological potential effects of SN on Multiple myeloma using a systems pharmacology approach.Methods: we collected putative targets of SN based on the Traditional Chinese Medicine System Pharmacology database，and oral bioavailability and drug-likeness was screened using absorption, distribution, metabolism, and excretion (ADME) criteria. the network of the interactions among the putative targets of SN and known therapeutic targets of Multiple myeloma was built by using the STITCH database. Then, topological parameters, “Degree” ,“Closeness” and“Betweenness” were calculated to identify the hub targets in the network. Furthermore, the hub targets were imported to the Database for Annotation, Visualization and Integrated Discovery to perform a pathway enrichment analysis.Results: 60 of the identified potential targets of the SN were also Multiple Myeloma- related targets, including 14 putative targets of SN were observed to be major hubs in terms of topological importance.Additionally,the results of pathway enrichment analysis indicated that targets of SN in treating Multiple Myeloma were mainly clustered into multiple biological processes by activating on several signaling pathways(PI3K-Akt, p38-MAPK, Ras/Raf/MEK/ERK pathways), which implied that these were involved in the underlying mechanisms of SN on Multiple Myeloma. Conclusions: Our works successfully explain the potential effects of SN for Multiple Myeloma treatment via the molecular mechanisms predicted by network pharmacology.Moreover,our present outcomes might shed light on the further clinical application of SN in treating Multiple Myeloma.

scholarly journals A Network Pharmacology Approach to Understanding the Mechanisms of Action of Traditional Medicine: Rheum L. for Diabetic Kidney Disease

2020 ◽  
Author(s):  
Jinli Luo ◽  
Chunli Piao ◽  
De Jin ◽  
Li Wang ◽  
Xiaohua Zhao ◽  
...  
Keyword(s):  
Kidney Disease ◽  
Diabetic Kidney Disease ◽  
Molecular Mechanisms ◽  
Chinese Herb ◽  
Enrichment Analysis ◽  
Peripheral Circulation ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Diabetic Kidney ◽  
Underlying Mechanisms

Abstract BackgroundRheum L. (Da-huang in pinyin, Radix Rhei Et Rhizome in pharmaceutical name), a classic Chinese herb, has been extensively used to treat diabetic kidney disease in clinical practice in China for many years. However, the pharmacological mechanisms of Rheum L. remain elusive. To decrypt the underlying mechanisms of Rheum L. in the treatment of diabetic kidney disease using a systems pharmacology approach. MethodsA network pharmacology-based strategy was proposed to elucidate the underlying multi-component, multi-target, and multi-pathway mode of action of Rheum L. against diabetic kidney disease. We collected putative targets of Rheum L. and a network of the interactions among the putative targets of Rheum L. and known therapeutic targets of diabetic kidney disease was built. The major hubs were imported to the Database to perform a pathway enrichment analysis. ResultsA total of 6 active ingredients and 271 targets of Rheum L. were picked out. 11 cellular biological processes and 18 pathways of Rheum L. mostly associated with inflammatory response, apoptosis, fibrosis, and peripheral circulation. ConclusionsRheum L. could alleviate diabetic kidney disease via the molecular mechanisms predicted by network pharmacology.

scholarly journals Analysis of MCM Proteins’ Role as a Potential Target of Statins in Patients with Acute Type A Aortic Dissection through Bioinformatics

Genes ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 387
Author(s):  
Zheyong Liang ◽  
Yongjian Zhang ◽  
Qiang Chen ◽  
Junjun Hao ◽  
Haichen Wang ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Molecular Mechanisms ◽  
Vascular Diseases ◽  
Enrichment Analysis ◽  
Type A ◽  
Protective Role ◽  
Gene Expression Omnibus ◽  
Pathway Enrichment Analysis ◽  
Acute Type ◽  
Type A Aortic Dissection

Acute aortic dissection is one of the most severe vascular diseases. The molecular mechanisms of aortic expansion and dissection are unclear. Clinical studies have found that statins play a protective role in aortic dissection development and therapy; however, the mechanism of statins’ effects on the aorta is unknown. The Gene Expression Omnibus (GEO) dataset GSE52093, GSE2450and GSE8686 were analyzed, and genes expressed differentially between aortic dissection samples and normal samples were determined using the Networkanalyst and iDEP tools. Weight gene correlation network analysis (WGCNA), functional annotation, pathway enrichment analysis, and the analysis of the regional variations of genomic features were then performed. We found that the minichromosome maintenance proteins (MCMs), a family of proteins targeted by statins, were upregulated in dissected aortic wall tissues and play a central role in cell-cycle and mitosis regulation in aortic dissection patients. Our results indicate a potential molecular target and mechanism for statins’ effects in patients with acute type A aortic dissection.

scholarly journals Metabonomic-Transcriptome Integration Analysis on Osteoarthritis and Rheumatoid Arthritis

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Ningyang Gao ◽  
Li Ding ◽  
Jian Pang ◽  
Yuxin Zheng ◽  
Yuelong Cao ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Gap Junction ◽  
Molecular Mechanisms ◽  
Linear Models ◽  
Principal Component ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Nf Kappa B ◽  
Linear Module ◽  
Hedgehog Acyltransferase

Purpose. This study is aimed at exploring the potential metabolite/gene biomarkers, as well as the differences between the molecular mechanisms, of osteoarthritis (OA) and rheumatoid arthritis (RA). Methods. Transcriptome dataset GSE100786 was downloaded to explore the differentially expressed genes (DEGs) between OA samples and RA samples. Meanwhile, metabolomic dataset MTBLS564 was downloaded and preprocessed to obtain metabolites. Then, the principal component analysis (PCA) and linear models were used to reveal DEG-metabolite relations. Finally, metabolic pathway enrichment analysis was performed to investigate the differences between the molecular mechanisms of OA and RA. Results. A total of 976 DEGs and 171 metabolites were explored between OA samples and RA samples. The PCA and linear module analysis investigated 186 DEG-metabolite interactions including Glycogenin 1- (GYG1-) asparagine_54, hedgehog acyltransferase- (HHAT-) glucose_70, and TNF receptor-associated factor 3- (TRAF3-) acetoacetate_35. Finally, the KEGG pathway analysis showed that these metabolites were mainly enriched in pathways like gap junction, phagosome, NF-kappa B, and IL-17 pathway. Conclusions. Genes such as HHAT, GYG1, and TRAF3, as well as metabolites including glucose, asparagine, and acetoacetate, might be implicated in the pathogenesis of OA and RA. Metabolites like ethanol and tyrosine might participate differentially in OA and RA progression via the gap junction pathway and phagosome pathway, respectively. TRAF3-acetoacetate interaction may be involved in regulating inflammation in OA and RA by the NF-kappa B and IL-17 pathway.

scholarly journals Elucidation of the mechanisms and molecular targets of Qishen Yiqi formula for the treatment of pulmonary arterial hypertension using a bioinformatics/network topology-based strategy

2020 ◽  
Vol 23 ◽  
Author(s):  
Peiliang Wu ◽  
Xiaona Xie ◽  
Mayun Chen ◽  
Junwei Sun ◽  
Luqiong Cai ◽  
...  
Keyword(s):  
Pulmonary Arterial Hypertension ◽  
Arterial Hypertension ◽  
Network Topology ◽  
Molecular Mechanisms ◽  
Molecular Targets ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Bioactive Ingredients ◽  
Pulmonary Arterial

Background and Objective: Qishen Yiqi formula (QSYQ) is used to treat cardiovascular disease in the clinical practice of traditional Chinese medicine. However, few studies have explored whether QSYQ affects pulmonary arterial hypertension (PAH), and the mechanisms of action and molecular targets of QSYQ for the treatment of PAH are unclear. A bioinformatics/network topology-based strategy was used to identify the bioactive ingredients, putative targets, and molecular mechanisms of QSYQ in PAH. Methods: A network pharmacology-based strategy was employed by integrating active component gathering, target prediction, PAH gene collection, network topology, and gene enrichment analysis to systematically explore the multicomponent synergistic mechanisms. Results: In total, 107 bioactive ingredients of QSYQ and 228 ingredient targets were identified. Moreover, 234 PAH-related differentially expressed genes with a |fold change| >2 and an adjusted P value < 0.005 were identified between the PAH patient and control groups, and 266 therapeutic targets were identified. The pathway enrichment analysis indicated that 85 pathways, including the PI3K-Akt, MAPK, and HIF-1 signaling pathways, were significantly enriched. TP53 was the core target gene, and 7 other top genes (MAPK1, RELA, NFKB1, CDKN1A, AKT1, MYC, and MDM2) were the key genes in the gene-pathway network based on the effects of QSYQ on PAH. Conclusion: An integrative investigation based on network pharmacology may elucidate the multicomponent synergistic mechanisms of QSYQ in PAH and lay a foundation for further animal experiments, human clinical trials and rational clinical applications of QSYQ.

scholarly journals Bioinformatic analysis identifies potential biomarkers and therapeutic targets of septic-shock-associated acute kidney injury

Hereditas ◽  
2021 ◽  
Vol 158 (1) ◽  
Author(s):  
Yun Tang ◽  
Xiaobo Yang ◽  
Huaqing Shu ◽  
Yuan Yu ◽  
Shangwen Pan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Septic Shock ◽  
Acute Kidney Injury ◽  
Molecular Mechanisms ◽  
Therapeutic Targets ◽  
Kidney Injury ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Blood Samples ◽  
Potential Biomarkers

Abstract Background Sepsis and septic shock are life-threatening diseases with high mortality rate in intensive care unit (ICU). Acute kidney injury (AKI) is a common complication of sepsis, and its occurrence is a poor prognostic sign to septic patients. We analyzed co-differentially expressed genes (co-DEGs) to explore relationships between septic shock and AKI and reveal potential biomarkers and therapeutic targets of septic-shock-associated AKI (SSAKI). Methods Two gene expression datasets (GSE30718 and GSE57065) were downloaded from the Gene Expression Omnibus (GEO). The GSE57065 dataset included 28 septic shock patients and 25 healthy volunteers and blood samples were collected within 0.5, 24 and 48 h after shock. Specimens of GSE30718 were collected from 26 patients with AKI and 11 control patents. AKI-DEGs and septic-shock-DEGs were identified using the two datasets. Subsequently, Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed to elucidate molecular mechanisms of DEGs. We also evaluated co-DEGs and corresponding predicted miRNAs involved in septic shock and AKI. Results We identified 62 DEGs in AKI specimens and 888, 870, and 717 DEGs in septic shock blood samples within 0.5, 24 and 48 h, respectively. The hub genes of EGF and OLFM4 may be involved in AKI and QPCT, CKAP4, PRKCQ, PLAC8, PRC1, BCL9L, ATP11B, KLHL2, LDLRAP1, NDUFAF1, IFIT2, CSF1R, HGF, NRN1, GZMB, and STAT4 may be associated with septic shock. Besides, co-DEGs of VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 coupled with corresponding predicted miRNAs, especially miR-29b-3p, miR-152-3p, and miR-223-3p may be regarded as promising targets for the diagnosis and treatment of SSAKI in the future. Conclusions Septic shock and AKI are related and VMP1, SLPI, PTX3, TIMP1, OLFM4, LCN2, and S100A9 genes are significantly associated with novel biomarkers involved in the occurrence and development of SSAKI.

scholarly journals Gene Expression Profile of Active HE4 Stimulation in Epithelial Ovarian Cancer Cells: Microarray Study and Comprehensive Bioinformatics Analysis

2020 ◽  
Author(s):  
Liancheng Zhu ◽  
Mingzi Tan ◽  
Haoya Xu ◽  
Bei Lin
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Clinical Significance ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Coexpression Analysis ◽  
Pathway Enrichment

Abstract Background.Human Epididymis Protein 4 (HE4) is a novel serum biomarker for diagnosis of epithelial ovarian cancer (EOC) with high specificity and sensitivity compared with CA125, and the increasing researches have been carried out on its roles in promoting carcinogenesis and chemoresistance in EOC in recent years, however, its underlying molecular mechanisms remain poorly understood. The aim of this study was to elucidate the molecular mechanisms of HE4 stimulation and to identify the key genes and pathways mediating carcinogenesis in EOC using microarray and bioinformatics analysis.Methods. We established a stable HE4-silence ES-2 ovarian cancer cell line labeled as “S”, and its active HE4 protein stimulated cells labeled as “S4”. Human whole genome microarray analysis was used to identify deferentially expressed genes (DEGs) from triplicate samples of S4 and S cells. “clusterProfiler” package in R, DAVID, Metascape, and Gene Set Enrichment Analysis (GSEA) were used to perform gene ontology (GO) and pathway enrichment analysis, and cBioPortal for WFDC2 coexpression analysis. GEO dataset (GSE51088) and quantitative real-time polymerase chain reaction (qRT-PCR) was applied for validation. The protein–protein interaction (PPI) network and modular analyses were performed using Metascape and Cytoscape. Results.In total, 713 DEGs were found (164 up regulated and 549 down regulated) and further analyzed by GO, pathway enrichment and PPI analyses. We found that MAPK pathway accounted for a significant portion of the enriched terms. WFDC2 coexpression analysis revealed ten WFDC2 coexpressed genes (TMEM220A, SEC23A, FRMD6, PMP22, APBB2, DNAJB4, ERLIN1, ZEB1, RAB6B, and PLEKHF1) that were also dramatically changed in S4 cells and validated by dataset GSE51088. Kaplan–Meier survival statistics revealed clinical significance for all of the 10 target genes. Finally, PPI was constructed, sixteen hub genes and eight molecular complex detections (MCODEs) were identified, the seeds of five most significant MCODEs were subjected to GO and KEGG enrichment analysis and their clinical significance was evaluated.Conclusions.By applying microarray and bioinformatics analyses, we identified DEGs and determined a comprehensive gene network of active HE4 stimulation in EOC cells. We offered several possible mechanisms and identified therapeutic and prognostic targets of HE4 in EOC.

scholarly journals The TGFβ-induced phosphorylation and activation of p38 mitogen-activated protein kinase is mediated by MAP3K4 and MAP3K10 but not TAK1

Open Biology ◽  
2013 ◽  
Vol 3 (6) ◽  
pp. 130067 ◽  
Author(s):  
Gopal P. Sapkota
Keyword(s):  
Protein Kinase ◽  
P38 Mapk ◽  
Transforming Growth Factor Beta ◽  
Molecular Mechanisms ◽  
Epithelial To Mesenchymal Transition ◽  
Transforming Growth Factor ◽  
Mitogen Activated Protein Kinase ◽  
Mapk Phosphorylation ◽  
Mesenchymal Transition ◽  
Mitogen Activated Protein

The signalling pathways downstream of the transforming growth factor beta (TGFβ) family of cytokines play critical roles in all aspects of cellular homeostasis. The phosphorylation and activation of p38 mitogen-activated protein kinase (MAPK) has been implicated in TGFβ-induced epithelial-to-mesenchymal transition and apoptosis. The precise molecular mechanisms by which TGFβ cytokines induce the phosphorylation and activation of p38 MAPK are unclear. In this study, I demonstrate that TGFβ-activated kinase 1 (TAK1/MAP3K7) does not play a role in the TGFβ-induced phosphorylation and activation of p38 MAPK in MEFs and HaCaT keratinocytes. Instead, RNAi -mediated depletion of MAP3K4 and MAP3K10 results in the inhibition of the TGFβ-induced p38 MAPK phosphorylation. Furthermore, the depletion of MAP3K10 from cells homozygously knocked-in with a catalytically inactive mutant of MAP3K4 completely abolishes the TGFβ-induced phosphorylation of p38 MAPK, implying that among MAP3Ks, MAP3K4 and MAP3K10 are sufficient for mediating the TGFβ-induced activation of p38 MAPK.

Gene expression profiles following active HE4 stimulation in epithelial ovarian cancer cells: microarray study and comprehensive bioinformatics analysis

2020 ◽  
Author(s):  
Liancheng Zhu ◽  
Mingzi Tan ◽  
Haoya Xu ◽  
Bei Lin
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Coexpression Analysis ◽  
Pathway Enrichment

Abstract Background: Human epididymis protein 4 (HE4) is a novel serum biomarker for diagnosing epithelial ovarian cancer (EOC) with high specificity and sensitivity, compared with CA125. Recent studies have focused on the roles of HE4 in promoting carcinogenesis and chemoresistance in EOC; however, the molecular mechanisms underlying its action remain poorly understood. This study was conducted to determine the molecular mechanisms underlying HE4 stimulation and identifying key genes and pathways mediating carcinogenesis in EOC by microarray and bioinformatics analysis.Methods: We established a stable HE4-silenced ES-2 ovarian cancer cell line labeled as “S”; the S cells were stimulated with the active HE4 protein, yielding cells labeled as “S4”. Human whole-genome microarray analysis was used to identify differentially expressed genes (DEGs) in S4 and S cells. The “clusterProfiler” package in R, DAVID, Metascape, and Gene Set Enrichment Analysis were used to perform gene ontology (GO) and pathway enrichment analysis, and cBioPortal was used for WFDC2 coexpression analysis. The GEO dataset (GSE51088) and quantitative real-time polymerase chain reaction were used to validate the results. Protein–protein interaction (PPI) network and modular analyses were performed using Metascape and Cytoscape, respectively. Results: In total, 713 DEGs were identified (164 upregulated and 549 downregulated) and further analyzed by GO, pathway enrichment, and PPI analyses. We found that the MAPK pathway accounted for a significant large number of the enriched terms. WFDC2 coexpression analysis revealed ten WFDC2-coexpressed genes (TMEM220A, SEC23A, FRMD6, PMP22, APBB2, DNAJB4, ERLIN1, ZEB1, RAB6B, and PLEKHF1) whose expression levels were dramatically altered in S4 cells; this was validated using the GSE51088 dataset. Kaplan–Meier survival statistics revealed that all 10 target genes were clinically significant. Finally, in the PPI network, 16 hub genes and 8 molecular complex detections (MCODEs) were identified; the seeds of the five most significant MCODEs were subjected to GO and KEGG enrichment analyses and their clinical relevance was evaluated.Conclusions: Through microarray and bioinformatics analyses, we identified DEGs and determined a comprehensive gene network following active HE4 stimulation in EOC cells. We proposed several possible mechanisms underlying the action of HE4 and identified the therapeutic and prognostic targets of HE4 in EOC.

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