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520 results on '"Huang, Xinsheng"'

55. Image Quality Assessment Based on Wavelet Coefficients Using Neural Network

Author

Yue, Dongxue, Huang, Xinsheng, Tan, Hongli, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Rangan, C. Pandu, editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Liu, Derong, editor, Fei, Shumin, editor, Hou, Zengguang, editor, Zhang, Huaguang, editor, and Sun, Changyin, editor

Published
2007
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70. Identification of Novel Kinase–Transcription Factor–mRNA–miRNA Regulatory Network in Nasopharyngeal Carcinoma by Bioinformatics Analysis

Author

Gao,Li, Zhou,Lei, and Huang,Xinsheng

Subjects
International Journal of General Medicine
Abstract

Li Gao,1 Lei Zhou,2 Xinsheng Huang2 1Department of Otolaryngology, Head and Neck Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan; 2Department of Otolaryngology-Head and Neck Surgery, Shanghai Zhongshan Hospital Affiliated to Fudan University, Shanghai, People’s Republic of ChinaCorrespondence: Xinsheng HuangDepartment of Otolaryngology-Head and Neck Surgery, Shanghai Zhongshan Hospital Affiliated to Fudan University, Shanghai, 200032, People’s Republic of ChinaTel/Fax +86-21-64041990Email huang.xinsheng@zs-hospital.sh.cnPurpose: Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors of the head and neck. This study aimed to investigate the crucial genes and regulatory networks involved in the carcinogenesis of NPC using a bioinformatics approach.Methods: Five mRNA and two miRNA expression datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and miRNAs (DEMs) between NPC and normal samples were analyzed using R software. The WebGestalt tool was used for functional enrichment analysis, and protein–protein interaction (PPI) network analysis of DEGs was performed using STRING database. Transcription factors (TFs) were predicted using TRRUST and Transcriptional Regulatory Element Database (TRED). Kinases were identified using X2Kgui. The miRNAs of DEGs were predicted using miRWalk database. A kinase–TF–mRNA–miRNA integrated network was constructed, and hub nodes were selected. The hub genes were validated using NPC datasets from the GEO and Oncomine databases. Finally, candidate small-molecule agents were predicted using CMap.Results: A total of 122 DEGs and 44 DEMs were identified. DEGs were associated with the immune response, leukocyte activation, endoplasmic reticulum stress in GO analysis, and the NF-κB signaling pathway in KEGG analysis. Four significant modules were identified using PPI network analysis. Subsequently, 26 TFs, 73 kinases, and 2499 miRNAs were predicted. The predicted miRNAs were cross-referenced with DEMs, and seven overlapping miRNAs were selected. In the kinase–TF–mRNA–miRNA integrated network, eight genes (PTGS2, FN1, MMP1, PLAU, MMP3, CD19, BMP2, and PIGR) were identified as hub genes. Hub genes were validated with consistent results, indicating the reliability of our findings. Finally, six candidate small-molecule agents (phenoxybenzamine, luteolin, thioguanosine, reserpine, blebbistatin, and camptothecin) were predicted.Conclusion: We identified DEGs and an NPC regulatory network involving kinases, TFs, mRNAs, and miRNAs, which might provide promising insight into the pathogenesis, treatment, and prognosis of NPC.Keywords: nasopharyngeal carcinoma, differentially expressed genes, microRNA, transcription factor, kinase, bioinformatics

Published
2021

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