Regulation of EMT in lung cancer cells by interaction of Hsp90 and SIRT1 / 国际肿瘤学杂志

Objective:To investigate the interaction between heat shock protein 90 (Hsp90) and silent mating-type information regulation 2 homolog 1 (SIRT1) and evaluate its effect on epithelial-mesenchymal transition (EMT) of lung cancer A549 cells.Methods:EMT model was established by treating lung cancer A549 cells with 5 μg/L transforming growth factor-β1 (TGF-β1), which was used as TGF-β1 group, and the normal lung cancer A549 cells were used as control group. The interaction between Hsp90 and SIRT1 in lung cancer A549 cells was detected by immunocoprecipitation method. The expression of Hsp90 gene was silenced by RNA interference technique, and the cells were divided into TGF-β1 group, TGF-β1+ siRNA-Hsp90-neg group and TGF-β1+ siRNA-Hsp90 group. Transwell invasion assay was used to investigate the effect of the interaction of Hsp90 and SIRT1 on the invasion ability of lung cancer A549 cells. The expressions of Hsp90, SIRT1, E-cadherin and vimentin were detected by Western blotting. The effect of inhibiting Hsp90 expression on the stability of SIRT1 protein and EMT of lung cancer A549 cells was observed.Results:After 48 h induction with TGF-β1, EMT characteristics of lung cancer A549 cells were induced successfully. The relative expression levels of Hsp90 protein in the control group and TGF-β1 group were 0.45±0.05 and 1.31±0.06, respectively, the relative expression levels of SIRT1 protein were 0.29±0.04 and 0.95±0.08, respectively, and there were statistically signigicant differences ( t=10.98, P=0.018; t=7.39, P=0.028). The results of immunocoprecipitation showed that there was an interaction between Hsp90 and SIRT1 protein in lung cancer A549 cells. The relative expression levels of Hsp90 in the TGF-β1 group, TGF-β1+ siRNA-Hsp90-neg group and TGF-β1+ siRNA-Hsp90 group were 0.75±0.07, 0.63±0.06 and 0.23±0.05, respectively, and there was a statistically significant difference ( F=18.85, P=0.012). The relative expression levels of SIRT1 in the above three groups were 0.99±0.08, 0.97±0.12 and 0.35±0.05, respectively, and there was a statistically significant difference ( F=16.52, P=0.014). The expression levels of Hsp90 and SIRT1 in the TGF-β1+ siRNA-Hsp90 group were significantly lower than those in the TGF-β1 group ( P=0.019, P=0.016). The numbers of cells passing Matrigel in the above three groups were 378.13±27.70, 323.52±19.82 and 142.51±22.54, respectively, and there was a statistically significant difference ( F=27.35, P=0.022). The number of cells passing Matrigel in the TGF-β1+ siRNA-Hsp90 group was significantly less than that in the TGF-β1 group ( P=0.028). The relative expression levels of E-cadherin in the above three groups were 0.31±0.02, 0.34±0.04 and 0.63±0.05, respectively, and there was a statistically significant difference ( F=19.39, P=0.031). The relative expression levels of vimentin in the above three groups were 0.33±0.02, 0.27±0.05 and 0.09±0.03, respectively, and there was a statistically significant difference ( F=12.58, P=0.012). The expression level of E-cadherin in the TGF-β1+ siRNA-Hsp90 group was significantly higher than that in the TGF-β1 group ( P=0.017), while the expression level of vimentin was significantly lower than that in the TGF-β1 group ( P=0.023). Conclusion:Hsp90 interacts with SIRT1, and Hsp90 inhibition can lead to the decrease of SIRT1 protein level. Hsp90 may play a role of molecular chaperone to maintain the conformation stability of SIRT1, and the interaction between Hsp90 and SIRT1 may be one of the molecular mechanisms for the occurrence of EMT and the enhancement of invasion ability of lung cancer A549 cells.

Immune system and zinc are associated with recurrent aphthous stomatitis: an assessment using a network-based approach

OBJECTIVE: The aim of this research was to identify genes, proteins and processes from the biomedical information published on recurrent aphthous stomatitis (RAS) using network-based foci. METHODS: The clinical context was defined using MeSH terms for RAS and biomarkers, combined with words associated with risk. A set of protein coding genes was prioritized using the Génie web server and classified with PANTHER. For defining biologically relevant proteins, protein-protein interaction networks were constructed using Reactome database and Cytoscape. Top 20 proteins were then subjected to functional enrichment using STRING. RESULTS: From 1,075,576 gene-abstract links, 1,491 genes were prioritized. Proteins were related to signaling molecule proteins (n=221), receptor proteins (n=221) and nucleic acid binding proteins (n=169). The network constructed with these proteins included 3,963 nodes and functional analysis showed that main processes involved immune system and zinc ion binding function. CONCLUSIONS: For the first time, bioinformatics tools were used for integrating pathways and networks associated with RAS. Molecules and processes associated with immune system recur robustly in all analyzed information. The molecular zinc ion binding function could be an area for exploring more specific and effective therapeutic interventions

Identification of therapeutic target genes with DNA microarray in multiple myeloma cell line treated by IKKβ/NF-κB inhibitor

PURPOSE: To explore the mechanism of resistance to IKKβ inhibitor in multiple myeloma (MM) cells and uncover novel therapeutic targets for MM. METHODS: We downloaded the microarray data (GSE8476) from GEO (Gene Expression Omnibus) database. The data were derived from the human MM cells lines (L363 cells) treated with IKKβ inhibitor MLN120b (MLN) for eight, 12 and 24 hours. Furthermore, we applied the Search Tool for the Retrieval of Interacting Genes (STRING) and Expression Analysis Systematic Explorer (EASE) database to construct protein-protein interaction networks and identified over-represented pathway among DEGs (differentially expressed genes). RESULTS: We obtained 108 DGEs in 8h vs. 12h group and 101 ones in 8h vs. 24h group. Most of DGEs were found to be involved in biological regulation. The significant pathways were Ig A pathway and the CAMs pathways. In addition, 24 common DGEs were found in the networks of the two groups such as ICAM 3 and SELL. CONCLUSION: Intercellular adhesion molecule 3 and SELL may be potential targets in multiple myeloma treatment in the future. .