scholarly journals CDC20 as a new therapeutic target for treating ovarian cancer: an integrated bioinformatics analysis

2021 ◽  
Author(s):  
Xiaocui Zhang ◽  
Fangfang Bi ◽  
Qing Yang
Keyword(s):  
Cell Cycle ◽  
Ovarian Cancer ◽  
Signaling Pathway ◽  
Therapeutic Target ◽  
Bioinformatics Analysis ◽  
Therapeutic Targets ◽  
Gene Set Enrichment Analysis ◽  
Transcription Activator ◽  
Pathway Enrichment ◽  
Oncomine Database

Abstract Background: There were 313959 cases of newly diagnosed ovarian cancer (OC) and 207252 new deaths for OC in 2020 and OC lacks effective treatment options. Therefore, identifying novel therapeutic targets is imminent. Here, we use an integrated bioinformatics analysis to key genes involved in ovarian cancer and reveal potential therapeutic targets.Methods: GSE105437, GSE14407 and GSE18520 downloaded from Gene Expression Omnibus (GEO) were used to screen differentially expressed genes (DEGs). Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to predict the potential functions of the DEGs. Protein-protein interaction network (PPI) was drawn through STRING database and select CDC20 having the highest degrees of connectivity as the potential therapeutic target. Oncomine database and quantitative Real-time RT-PCR (RT-qPCR) of the ovarian tissues were used to validate the mRNA expression of CDC20. We use Gene Set Enrichment Analysis (GSEA) software to explore the potential biological function of CDC20 in OC. Results: A total of 821 DEGs were obtained, including 497 upregulated genes and 324 downregulated genes. Functional and pathway enrichment analyses indicated the DEGs were mainly involved in DNA-binding transcription activator activity, tubulin binding, microtubule binding, cell cycle, Wnt signaling pathway, p53 signaling pathway, and metabolism changes. Oncomine database analysis and RT-qPCR showed that CDC20 is significantly upregulated in OC tissues. GSEA analysis showed that CDC20 may regulate OC via cell cycle, citrate and TCA cycle, Oxidative phosphorylation and ubiquitin mediated proteolysis pathways. Conclusion: The results of the present study deduced that CDC20 is overexpressed in OC and may be a promising therapeutic target for the treatment of OC.

scholarly journals CDC20 as a new therapeutic target for treating ovarian cancer: an integrated bioinformatics analysis

2021 ◽  
Author(s):  
Xiaocui Zhang ◽  
Fangfang Bi ◽  
Qing Yang
Keyword(s):  
Cell Cycle ◽  
Ovarian Cancer ◽  
Signaling Pathway ◽  
Therapeutic Target ◽  
Bioinformatics Analysis ◽  
Therapeutic Targets ◽  
Gene Set Enrichment Analysis ◽  
Transcription Activator ◽  
Pathway Enrichment ◽  
Oncomine Database

Abstract Background There were 313959 cases of newly diagnosed ovarian cancer (OC) and 207252 new deaths for OC in 2020 and OC lacks effective treatment options. Therefore, identifying novel therapeutic targets is imminent. Here, we use an integrated bioinformatics analysis to key genes involved in ovarian cancer and reveal potential therapeutic targets. Methods GSE105437, GSE14407 and GSE18520 downloaded from Gene Expression Omnibus (GEO) were used to screen differentially expressed genes (DEGs). Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to predict the potential functions of the DEGs. Protein-protein interaction network (PPI) was drawn through STRING database and select CDC20 having the highest degrees of connectivity as the potential therapeutic target. Oncomine database and quantitative Real-time RT-PCR (RT-qPCR) of the ovarian tissues were used to validate the mRNA expression of CDC20. We use Gene Set Enrichment Analysis (GSEA) software to explore the potential biological function of CDC20 in OC. Results A total of 821 DEGs were obtained, including 497 upregulated genes and 324 downregulated genes. Functional and pathway enrichment analyses indicated the DEGs were mainly involved in DNA-binding transcription activator activity, tubulin binding, microtubule binding, cell cycle, Wnt signaling pathway, p53 signaling pathway, and metabolism changes. Oncomine database analysis and RT-qPCR showed that CDC20 is significantly upregulated in OC tissues. GSEA analysis showed that CDC20 may regulate OC via cell cycle, citrate and TCA cycle, Oxidative phosphorylation and ubiquitin mediated proteolysis pathways. Conclusion The results of the present study deduced that CDC20 is overexpressed in OC and may be a promising therapeutic target for the treatment of OC.

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.

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.

CENPF/CDK1 Signaling Pathway Enhances the Progression of Adrenocortical Carcinoma by Regulating the G2/M-phase Cell Cycle

2021 ◽  
Author(s):  
Yugang Huang ◽  
Dan Li ◽  
Li Wang ◽  
Xiaomin Su ◽  
Xian-bin Tang
Keyword(s):  
Cell Cycle ◽  
Signaling Pathway ◽  
Adrenocortical Carcinoma ◽  
Immune Cell ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Phase Cell ◽  
Aberrant Expression ◽  
M Phase

Abstract Adrenocortical carcinoma (ACC) is an aggressive and rare malignant tumor and prone to local invasion and metastasis. While, overexpressed Centromere Protein F (CENPF) is closely related to oncogenesis of various neoplasms, including ACC. However, the prognosis and exact biological function of CENPF in ACC remains largely unclear. In present essay, the expression of CENPF in human ACC samples, GEO and TCGA databases depicted that CENPF were overtly hyper-expressed in ACC patients and positively correlated with tumor stage. The aberrant expression of CENPF was significantly correlated with unfavorable overall survival (OS) in ACC patients. Then, the application of gene-set enrichment analysis (GSEA) declared that CENPF was mainly involved in the G2/M-phase mediated cell cycle and p53 signaling pathway. Further, a small RNA interference experiment was conducted to demonstrate that the interaction between CENPF and CDK1 enhanced the G2/M-phase transition of mitosis, cell proliferation and might induce p53 mediated anti-tumor effect in human ACC cell line, SW13 cells. Lastly, two available therapeutic strategies, including immunotherapy and chemotherapy, have been further probed. Immune infiltration analysis highlighted that ACC patients with high CENPF expression harbored significantly different immune cell populations, and high TMB/MSI score. Then, the gene-drug interaction network stated that CENPF inhibitors, such as Cisplatin, Sunitinib, and Etoposide, might serve as potential drugs for the therapy of ACC. Briefly, CENPF and related genes might be served as a novel prognostic biomarker or latent therapeutic target for ACC patients.

scholarly journals Exploration of Anti-Staphylococcus Aureus Activity and Molecular Mechanism of Wuweixiaoduyin using Network Pharmacology Anti-Staphylococcus Aureus Activity of Wuweixiaoduyin using Network Pharmacology

2021 ◽  
Author(s):  
Kai Huang ◽  
Bigyuan Lin ◽  
Haiyong Ren ◽  
Qifen Mao ◽  
Qiaofeng Guo ◽  
...  
Keyword(s):  
Staphylococcus Aureus ◽  
Growth Factor ◽  
Signaling Pathway ◽  
Target Genes ◽  
Therapeutic Targets ◽  
Mitogen Activated Protein Kinase ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Pathway Enrichment ◽  
Aureus Infection

Abstract Background:S. aureus (Staphylococcus aureus) infection imposes a serious burden to global healthcare systems. WWXDY (Wuweixiaoduyin) is a traditional Chinese medicine, and it is usually used to treat infections in China. This study aimed to explore the active compounds, therapeutic targets, key pathways, and potential mechanisms of WWXDY in the treatment of S. aureus infection. Materials & Methods:Data related to active compounds and therapeutic targets of WWXDY for treating S. aureus were collected from DisGeNET, GeneCards, and DrugBank databases. To explore the roles of the active targets in gene function and signaling pathways, KEGG (Kyoto Gene and Genomics Encyclopedia) pathway enrichment and GO (Gene Ontology) analyses of the 122 target genes in the PPI (protein-protein interaction) network were performed. We further performed NP (network pharmacology) by using a network analyzer to screen 30 key targets. Results:A total 92 active compounds of WWXDY were screened. The 122 overlapped genes were found from 785 therapeutic targets and 684 S. aureus-related genes. Besides, 92 active compounds of WWXDY, such as mandenol, ethyllinolenate, eriodyctiol, secologanic dibutylacetal_qt, etc., were identified. The PPI network of the effective ingredients of WWXDY in treating S. aureus infection identified the top 30 genes, including IL-6 (interleukin-6), TNF-α (tumor necrosis factor-α), VEGFA (vascular endothelial growth factor A), AKT1, CXCL8, MAPK3 (mitogen-activated protein kinase 3), TLR (toll-like receptor 4), IL-1β, EGFR (epidermal growth factor receptor), and MMP9 (matrix metalloproteinase-9). Conclusion:The GO functional and KEGG pathway enrichment analyses indicated that 122 overlapped genes were mainly enriched in COVID-19, AGE-RAGE signaling pathway, C-type lectin receptor signaling pathway, Pertussis, and Chagas disease. Our findings indicated the active compounds and therapeutic targets of WWXDY in treating S. aureus infection, as well as its potential mechanisms.

scholarly journals Krupple-Like Factor 5 is a Potential Therapeutic Target and Prognostic Marker in Epithelial Ovarian Cancer

2020 ◽  
Vol 11 ◽  
Author(s):  
Abdul K. Siraj ◽  
Poyil Pratheeshkumar ◽  
Sasidharan Padmaja Divya ◽  
Sandeep Kumar Parvathareddy ◽  
Khadija A. Alobaisi ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Cell Growth ◽  
Epithelial Ovarian Cancer ◽  
Signaling Pathway ◽  
Cell Lines ◽  
Therapeutic Target ◽  
Potential Therapeutic Target ◽  
Mesenchymal Transition ◽  
Stat3 Signaling ◽  
Stat3 Signaling Pathway

Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy. Despite current therapeutic and surgical options, advanced EOC shows poor prognosis. Identifying novel molecular therapeutic targets is highly needed in the management of EOC. Krupple-like factor 5 (KLF5), a zinc-finger transcriptional factor, is highly expressed in a variety of cancer types. However, its role and expression in EOC is not fully illustrated. Immunohistochemical analysis was performed to assess KLF5 protein expression in 425 primary EOC samples using tissue microarray. We also addressed the function of KLF5 in EOC and its interaction with signal transducer and activator of transcription 3 (STAT3) signaling pathway. We found that KLF5 overexpressed in 53% (229/425) of EOC samples, and is associated with aggressive markers. Forced expression of KLF5 enhanced cell growth in low expressing EOC cell line, MDAH2774. Conversely, knockdown of KLF5 reduced cell growth, migration, invasion and progression of epithelial to mesenchymal transition in KLF5 expressing cell lines, OVISE and OVSAHO. Importantly, silencing of KLF5 decreased the self-renewal ability of spheroids generated from OVISE and OVSAHO cell lines. In addition, downregulation of KLF5 potentiated the effect of cisplatin to induce apoptosis in these cell lines. These data reveals the pro-tumorigenic role of KLF5 in EOC and uncover its role in activation of STAT3 signaling pathway, suggesting the importance of KLF5 as a potential therapeutic target for EOC therapy.

scholarly journals Bioinformatic analysis reveals MIR502 as a potential tumour suppressor in ovarian cancer

2020 ◽  
Author(s):  
Yan Li ◽  
Qi Wang ◽  
Ning Ning ◽  
Fanglan Tang ◽  
Yan Wang
Keyword(s):  
Ovarian Cancer ◽  
Kegg Pathway ◽  
Tumour Suppressor ◽  
Signalling Pathway ◽  
Gene Set Enrichment Analysis ◽  
Screening Methods ◽  
Ppi Network ◽  
Pathway Enrichment ◽  
Core Proteins ◽  
Hippo Signalling

Abstract Background: Ovarian cancer (OC) is a major cause of death among women due to the lack of early screening methods and its complex pathological progression. Increasing evidence has indicated that microRNAs regulate gene expression in tumours by interacting with mRNAs. Although the research regarding OC and microRNAs is extensive, the vital role of MIR502 in OC remains unclear.Methods: We integrated two microRNA expression arrays from GEO to identify differentially expressed genes. The Kaplan–Meier method was used to screen for miRNAs that had an influence on survival outcome. Upstream regulators of MIR502 were predicted by JASPAR and verified by ChIP-seq data. The LinkedOmics database was used to study genes that were correlated with MIR502. Gene Set Enrichment Analysis (GSEA) was conducted for functional annotation with GO and KEGG pathway enrichment analyses by using the open access WebGestalt tool. We constructed a PPI network by using STRING to further explore the core proteins.Results: We found that the expression level of MIR502 was significantly downregulated in OC, which was related to poor overall survival. NRF1, as an upstream regulator of MIR502, was predicted by JASPAR and verified by ChIP-seq data. In addition, anti-apoptosis and pro-proliferation genes in the Hippo signalling pathway, including CCND1, MYC, FGF1 and GLI2, were negatively regulated by MIR502, as shown in the GO and KEGG pathway enrichment results. The PPI network further demonstrated that CCND1 and MYCN were at core positions in the development of ovarian cancer. Conclusions: MIR502, which is regulated by NRF1, acts as a tumour suppressor gene to accelerate apoptosis and suppress proliferation by targeting the Hippo signalling pathway in ovarian cancer.

scholarly journals Screening of Osteoarthritis-Related Genes and Function Determination Based on Bioinformatics Tools

2021 ◽  
Author(s):  
Zheng Fu ◽  
Weiqian Jiang ◽  
Wenlong Yan ◽  
Fei Xie ◽  
Yu Chen ◽  
...  
Keyword(s):  
Regulatory Networks ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Experimental Studies ◽  
Therapeutic Targets ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Pathway Enrichment ◽  
Early Diagnostic

Abstract Background:Osteoarthritis(OA), commonly seen in the middle-aged and elderly population, imposes a heavy burden on patients from the clinical, humanistic and economic aspects. Our work aims at the discovery of early diagnostic and therapeutic targets for OA and new candidate biomarkers for experimental studies on OA via bioinformatics analysis.Methods:The dataset GSE114007 was downloaded from GEO to identify differentially expressed genes(DEGs) in R using 3 different algorithms. Overlapping DEGs were subject to GO and KEGG pathway enrichment analysis and functional annotation. Following the identification of DEGs, a protein-protein interaction(PPI) network was established and imported into Cytoscape to screen for hubgenes. The expression of each hubgene was verified in two other datasets and create miRNA-mRNA regulatory networks.Results:174 upregulated genes and 117 downregulated genes were identified among the overlapping DEGs. According to the results of GO enrichment analysis,MF enrichment was basically found in ECM degradation and collagen breakdown; enrichment was also present in the development, ossification, and differentiation of cells. The KEGG pathway enrichment analysis suggested significant enrichment in such pathways as PI3K-AKT, P53, TNF, and FoxO. 23 hubgenes were obtained from the PPI network, and 11 genes were identified as DEGs through verification. 8 genes were used for the establishment of miRNA-mRNA regulatory networks.Conclusion:OA-related genes, proteins, pathways and miRNAs that were identified through bioinformatics analysis may provide a reference for the discovery of early diagnostic and therapeutic targets for OA, as well as candidate biomarkers for experimental studies on OA.

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