PPI Network Analysis of mRNA Expression Profile of Ezrin Knockdown in Esophageal Squamous Cell Carcinoma

Wu, Bing‐Li; Xie, Jian‐Jun; Du, Zhifeng; Wu, Jian‐Yi; Zhang, Pi‐Xian; Xu, Li; Li, En‐Min

doi:10.1155/2014/651954

Cited by 22 publications

(33 citation statements)

References 43 publications

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“…GSE6233) (42,43). Furthermore, consistent with this microarray data, immunohistochemical analysis of ESCC specimens and normal esophageal mucosae has demonstrated a negative correlation between ezrin levels and the level of ATF3 (42).…”

Section: Discussionsupporting

confidence: 79%

Ezrin Inhibition Up-regulates Stress Response Gene Expression

Çelik

Bulut

Han

et al. 2016

Journal of Biological Chemistry

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Ezrin is a member of the ERM (ezrin/radixin/moesin) family of proteins that links cortical cytoskeleton to the plasma membrane. High expression of ezrin correlates with poor prognosis and metastasis in osteosarcoma. In this study, to uncover specific cellular responses evoked by ezrin inhibition that can be used as a specific pharmacodynamic marker(s), we profiled global gene expression in osteosarcoma cells after treatment with small molecule ezrin inhibitors, NSC305787 and NSC668394. We identified and validated several up-regulated integrated stress response genes including PTGS2, ATF3, DDIT3, DDIT4, TRIB3, and ATF4 as novel ezrin-regulated transcripts. Analysis of transcriptional response in skin and peripheral blood mononuclear cells from NSC305787-treated mice compared with a control group revealed that, among those genes, the stress gene DDIT4/REDD1 may be used as a surrogate pharmacodynamic marker of ezrin inhibitor compound activity. In addition, we validated the antimetastatic effects of NSC305787 in reducing the incidence of lung metastasis in a genetically engineered mouse model of osteosarcoma and evaluated the pharmacokinetics of NSC305787 and NSC668394 in mice. In conclusion, our findings suggest that cytoplasmic ezrin, previously considered a dormant and inactive protein, has important functions in regulating gene expression that may result in down-regulation of stress response genes.

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Section: Discussionsupporting

confidence: 79%

Ezrin Inhibition Up-regulates Stress Response Gene Expression

Çelik

Bulut

Han

et al. 2016

Journal of Biological Chemistry

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“…Subsequently, network topological properties were analyzed to distinguish between the predicted network and a random network. A node degree approximating a power-law distribution is a standard characteristic of scale-free networks, and the PPI network in this study obeyed this rule (23,24). The 3 subnetworks were true complex biological networks characterized as scale-free, suggesting that the PPI network is reliable and robust.…”

Section: Discussionsupporting

confidence: 52%

Identification of core genes and prediction of miRNAs associated with osteoporosis using a bioinformatics approach

Chai

Tan

et al. 2018

Oncol Lett

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Osteoporosis (OP) is an age-related disease, and osteoporotic fracture is one of the major causes of disability and mortality in elderly patients (>70 years old). As the pathogenesis and molecular mechanism of OP remain unclear, the identification of disease biomarkers is important for guiding research and providing therapeutic targets. In the present study, core genes and microRNAs (miRNAs) associated with OP were identified. Differentially expressed genes (DEGs) between human mesenchymal stem cell specimens from normal osseous tissues and OP tissues were detected using the GEO2R tool of the Gene Expression Omnibus database and Morpheus. Network topological parameters were determined using NetworkAnalyzer. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery, and ClueGO. Cytoscape with the Search Tool for the Retrieval of Interacting Genes and Molecular Complex Detection plug-in was used to visualize protein-protein interactions (PPIs). Additionally, miRNA-gene regulatory modules were predicted using CyTargetLinker in order to guide future research. In total, 915 DEGs were identified, including 774 upregulated and 141 downregulated genes. Enriched GO terms and pathways were determined, including 'nervous system development', 'regulation of molecular function', 'glutamatergic synapse pathway' and 'pathways in cancer'. The node degrees of DEGs followed power-law distributions. A PPI network with 541 nodes and 1,431 edges was obtained. Overall, 3 important modules were identified from the PPI network. The following 10 genes were identified as core genes based on high degrees of connectivity: Albumin, PH domain leucine-rich repeat-containing protein phosphatase 2 (PHLPP2), DNA topoisomerase 2-α, kininogen 1 (KNG1), interleukin 2 (IL2), leucine-rich repeats and guanylate kinase domain containing, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit γ (PIK3CG), leptin, transferrin and RNA polymerase II subunit A (POLR2A). Additionally, 15 miRNA-target interactions were obtained using CyTargetLinker. Overall, 7 miRNAs co-regulated IL2, 3 regulated PHLPP2, 3 regulated KNG1, 1 regulated PIK3CG and 1 modulated POLR2A. These results indicate potential biomarkers in the pathogenesis of OP and therapeutic targets.

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“…It is generally acknowledged that the scale-free network could be judged according to the node degree distribution of a PPI network [22,38]. The node degree distributions of the total ROS related genes network followed power law fit distributions.…”

Section: Discussionmentioning

confidence: 99%

Transcriptomic Analysis Reveals Cu/Zn SODs Acting as Hub Genes of SODs in Hylocereus undatus Induced by Trypsin during Storage

Pang

Liu

et al. 2020

Antioxidants

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It has been revealed by us that superoxide scavenging is a new activity of trypsin. In this study, the synergistic mechanisms of trypsin and superoxide dismutases (SODs) were evaluated in Hylocereus undatus (pitaya). Trypsin significantly improved the storage quality of H. undatus, including weight loss impediment and decrease of cellular injury. The regulatory mechanisms of 16 SOD genes by trypsin were revealed using transcriptomic analysis on H. undatus. Results revealed that important physiological metabolisms, such as antioxidant activities or metal ion transport were induced, and defense responses were inhibited by trypsin. Furthermore, the results of protein-protein interaction (PPI) networks showed that besides the entire ROS network, the tiny SODs sub-network was also a scale-free network. Cu/Zn SODs acted as the hub that SODs synergized with trypsin during the storage of H. undatus.Trypsin is a widely used protease. It has been confirmed that trypsin significantly impacts on the free radical scavenging activities of flavonoids [8]. Our previous results also showed that trypsin scavenges superoxide anions (O 2 • − ) and protects cells [9].In the area of phytopathology, transcriptomic analysis has been successful used on lots of plants [10][11][12][13]. However, few of transcriptomic works have been focused on the preservation of fruits. The mechanisms of betalain biosynthesis have been investigated in H. undatus [2], and the concision analysis of antioxidant system induced by trypsin has also been investigated in our previous paper [14]. Considering the superoxide scavenging activity of trypsin, the function and synergistic mechanisms of trypsin with SODs impact on the quality of H. undatus during storage is an interesting work. The mechanisms of postharvest quality of fruits still need more works.Protein-protein interaction (PPI) networks analyses help us to figure out the regulatory mechanisms of proteins [15]. Plugins of Cytoscape, including NetworkAnalyzer, Molecular Complex Detection (MCODE), and cytoHubba, could score and rank the nodes or obtain clusters in the PPI network [16].In the current work, the regulatory mechanisms of trypsin on the H. undatus by cooperating with SODs were investigated. The changes in expression of SODs of H. undatus peels were analyzed. Analyses of gene ontology (GO) and KEGG enrichment of ROS or SOD related genes were performed, and the PPI network of ROS related genes and sub-network of SODs and their first neighbors were constructed. The hub genes of SODs regulated by trypsin during storage were further screened by cytoHubba and MCODE of cytoscape.

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PPI Network Analysis of mRNA Expression Profile of Ezrin Knockdown in Esophageal Squamous Cell Carcinoma

Cited by 22 publications

References 43 publications

Ezrin Inhibition Up-regulates Stress Response Gene Expression

Ezrin Inhibition Up-regulates Stress Response Gene Expression

Identification of core genes and prediction of miRNAs associated with osteoporosis using a bioinformatics approach

Transcriptomic Analysis Reveals Cu/Zn SODs Acting as Hub Genes of SODs in Hylocereus undatus Induced by Trypsin during Storage

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