YCYan Chen

Yan Chen

*This is an algorithmically generated author record based on publicly available information.

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Yan Chen has a total of 13 co-authors. Here are the top co-authors by number of shared publications:


Latest Publications

  • Open Access

    Survivin Regulates Bad Gene Expression by Binding to Its Promoter and Modulates Cell Cycle and Apoptosis in Esophageal Carcinoma Cell

    by Yan Chen, Shayahati Bieerkehazhi, Xiumei Li, Lili Ma, Waresijiang Yibulayin, Jihua Ran

    Esophageal cancer (EC) is the eighth most prevalent cancer and the sixth leading cause of cancer-related mortality worldwide. As an antiapoptotic and a proapoptotic protein, respectively, survivin and Bad play an important role in carcinogenesis of the most human cancers including EC. However, the regulatory relationships between them remain unclear. We sought to investigate the effects of survivin knockdown and overexpression on the expression of Bad gene, cell cycle progression, and apoptosis of esophageal carcinoma cell. The mRNA expression levels of survivin and Bad were determined in EC tissue samples. The knockdown and overexpression experiments were performed in ECA109 and KYSE450 cells via transfection with survivin overexpression and shRNA plasmids. A Bad overexpression experiment was conducted to confirm the biological effect on knockdown of survivin via modulating Bad expression. RT-qPCR and Western blot analysis were used to detect mRNA and protein expression, respectively. Cell cycle and apoptosis were analyzed by flow cytometry. The chromatin immunoprecipitation (ChIP) was conducted to determine the binding sites of survivin on the promoter of Bad gene. By analyzing the mRNA expression of survivin and Bad in 40 ESCC patient specimens, we found that the positive expression rate of survivin in tumor tissues (88%, 35/40) was remarkably high, compared with the distal nontumor tissues (48%, 19/40, < 0.01). On the other hand, the positive expression rate of Bad in tumor tissues (70%, 28/40) was remarkably low, compared with the distal nontumor tissues (95%, 38/40, < 0.01). Overexpression of survivin decreases Bad mRNA and protein expression and promotes transformation of cell cycle to S phase. Conversely, knockdown of survivin increases Bad mRNA and protein expression and induces cell cycle arrest and apoptosis. Bad overexpression inducing apoptosis of esophageal carcinoma cell shows the similar apoptotic effect with survivin knockdown. ChIP assays indicate that survivin directly binds to the Bad promoter region, diminishing the transcriptional activity of Bad. In conclusion, the result suggested that survivin regulates Bad gene expression by binding to its promoter and modulates cell cycle and apoptosis in esophageal carcinoma cell.


  • Open Access

    Construction and analysis of the protein-protein interaction network related to essential hypertension

    by Jihua Ran, Hui Li, Jianfeng Fu, Ling Liu, Yanchao Xing, Xiumei Li, Hongming Shen, Yan Chen, Xiaofang Jiang, Yan Li, et al.

    Background: Essential hypertension (EH) is a complex disease as a consequence of interaction between environmental factors and genetic background, but the pathogenesis of EH remains elusive. The emerging tools of network medicine offer a platform to explore a complex disease at system level. In this study, we aimed to identify the key proteins and the biological regulatory pathways involving in EH and further to explore the molecular connectivities between these pathways by the topological analysis of the Protein-protein interaction (PPI) network. Result: The extended network including one giant network consisted of 535 nodes connected via 2572 edges and two separated small networks. 27 proteins with high BC and 28 proteins with large degree have been identified. NOS3 with highest BC and Closeness centrality located in the centre of the network. The backbone network derived from high BC proteins presents a clear and visual overview which shows all important regulatory pathways for blood pressure (BP) and the crosstalk between them. Finally, the robustness of NOS3 as central protein and accuracy of backbone were validated by 287 test networks. Conclusion: Our finding suggests that blood pressure variation is orchestrated by an integrated PPI network centered on NOS3.