Gao Li, Zhou Lei, Huang Xinsheng
Department of Otolaryngology, Head and Neck Surgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Department of Otolaryngology-Head and Neck Surgery, Shanghai Zhongshan Hospital Affiliated to Fudan University, Shanghai, People's Republic of China.
Int J Gen Med. 2021 Oct 30;14:7453-7469. doi: 10.2147/IJGM.S327657. eCollection 2021.
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.
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.
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.
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.
鼻咽癌（NPC）是头颈部最常见的恶性肿瘤之一。本研究旨在采用生物信息学方法研究参与鼻咽癌发生发展的关键基因和调控网络。
从基因表达综合数据库（GEO）下载了5个mRNA和2个miRNA表达数据集。使用R软件分析鼻咽癌与正常样本之间的差异表达基因（DEGs）和miRNA（DEMs）。使用WebGestalt工具进行功能富集分析，并使用STRING数据库对DEGs进行蛋白质-蛋白质相互作用（PPI）网络分析。使用TRRUST和转录调控元件数据库（TRED）预测转录因子（TFs）。使用X2Kgui鉴定激酶。使用miRWalk数据库预测DEGs的miRNA。构建激酶-TF-mRNA-miRNA整合网络，并选择枢纽节点。使用来自GEO和Oncomine数据库的NPC数据集验证枢纽基因。最后，使用CMap预测候选小分子药物。
共鉴定出122个DEGs和44个DEMs。在基因本体（GO）分析中，DEGs与免疫反应、白细胞活化、内质网应激相关，在京都基因与基因组百科全书（KEGG）分析中与NF-κB信号通路相关。使用PPI网络分析鉴定出四个显著模块。随后，预测了26个TFs、73个激酶和2499个miRNA。将预测的miRNA与DEM进行交叉比对，选择了7个重叠的miRNA。在激酶-TF-mRNA-miRNA整合网络中，8个基因（PTGS2、FN1、MMP1、PLAU、MMP3、CD19、BMP2和PIGR）被鉴定为枢纽基因。枢纽基因得到了一致结果的验证，表明我们研究结果的可靠性。最后，预测了6种候选小分子药物（酚苄明、木犀草素、硫鸟嘌呤、利血平、肌球蛋白抑制剂和喜树碱）。
我们鉴定出了DEGs以及一个涉及激酶、TFs、mRNAs和miRNAs的鼻咽癌调控网络，这可能为鼻咽癌的发病机制、治疗和预后提供有前景的见解。
